Overview

Dataset statistics

Number of variables29
Number of observations110
Missing cells129
Missing cells (%)4.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.0 KiB
Average record size in memory233.2 B

Variable types

Numeric9
Categorical20

Alerts

airdate has constant value "2020-12-17" Constant
url has a high cardinality: 110 distinct values High cardinality
name has a high cardinality: 97 distinct values High cardinality
_embedded_show_url has a high cardinality: 84 distinct values High cardinality
_embedded_show_name has a high cardinality: 84 distinct values High cardinality
_embedded_show_premiered has a high cardinality: 64 distinct values High cardinality
_embedded_show_officialSite has a high cardinality: 77 distinct values High cardinality
_embedded_show_summary has a high cardinality: 75 distinct values High cardinality
_links_self_href has a high cardinality: 110 distinct values High cardinality
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
season is highly correlated with numberHigh correlation
number is highly correlated with season and 2 other fieldsHigh correlation
runtime is highly correlated with number and 2 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with number and 2 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
name is highly correlated with airdate and 1 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with _embedded_show_name and 11 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_name and 5 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
summary is highly correlated with _embedded_show_officialSite and 4 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 13 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 8 other fieldsHigh correlation
type is highly correlated with _embedded_show_officialSite and 4 other fieldsHigh correlation
_embedded_show_type is highly correlated with _embedded_show_officialSite and 6 other fieldsHigh correlation
airdate is highly correlated with name and 16 other fieldsHigh correlation
airtime is highly correlated with _embedded_show_name and 5 other fieldsHigh correlation
_embedded_show_status is highly correlated with _embedded_show_ended and 4 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
image is highly correlated with name and 16 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_embedded_show_language is highly correlated with _embedded_show_officialSite and 5 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with _embedded_show_officialSite and 5 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_name and 5 other fieldsHigh correlation
id is highly correlated with name and 12 other fieldsHigh correlation
name is highly correlated with id and 20 other fieldsHigh correlation
season is highly correlated with name and 9 other fieldsHigh correlation
number is highly correlated with name and 12 other fieldsHigh correlation
type is highly correlated with name and 9 other fieldsHigh correlation
airtime is highly correlated with airstamp and 9 other fieldsHigh correlation
airstamp is highly correlated with name and 14 other fieldsHigh correlation
runtime is highly correlated with id and 15 other fieldsHigh correlation
image is highly correlated with id and 22 other fieldsHigh correlation
summary is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_id is highly correlated with id and 18 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_type is highly correlated with name and 16 other fieldsHigh correlation
_embedded_show_language is highly correlated with airstamp and 8 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 20 other fieldsHigh correlation
_embedded_show_status is highly correlated with name and 15 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with name and 15 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with name and 13 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 23 other fieldsHigh correlation
_embedded_show_ended is highly correlated with id and 13 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 23 other fieldsHigh correlation
_embedded_show_weight is highly correlated with name and 13 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with name and 6 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_updated is highly correlated with id and 11 other fieldsHigh correlation
number has 3 (2.7%) missing values Missing
runtime has 10 (9.1%) missing values Missing
image has 78 (70.9%) missing values Missing
_embedded_show_runtime has 34 (30.9%) missing values Missing
_embedded_show_averageRuntime has 4 (3.6%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
image is uniformly distributed Uniform
_embedded_show_url is uniformly distributed Uniform
_embedded_show_name is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique

Reproduction

Analysis started2022-05-10 02:15:11.466889
Analysis finished2022-05-10 02:16:04.802133
Duration53.34 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014744.909
Minimum1732625
Maximum2289378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1008.0 B
2022-05-09T21:16:04.871382image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1732625
5-th percentile1951969.55
Q11980491
median1988632
Q32008336.75
95-th percentile2202065.05
Maximum2289378
Range556753
Interquartile range (IQR)27845.75

Descriptive statistics

Standard deviation82526.6339
Coefficient of variation (CV)0.0409613314
Kurtosis3.732099296
Mean2014744.909
Median Absolute Deviation (MAD)11707
Skewness1.230236556
Sum221621940
Variance6810645303
MonotonicityNot monotonic
2022-05-09T21:16:04.975366image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19888611
 
0.9%
19854711
 
0.9%
20000611
 
0.9%
20000601
 
0.9%
19975171
 
0.9%
19975161
 
0.9%
19909011
 
0.9%
19884031
 
0.9%
19856981
 
0.9%
19856971
 
0.9%
Other values (100)100
90.9%
ValueCountFrequency (%)
17326251
0.9%
18065901
0.9%
19499101
0.9%
19499111
0.9%
19503671
0.9%
19507011
0.9%
19535201
0.9%
19607281
0.9%
19628911
0.9%
19639981
0.9%
ValueCountFrequency (%)
22893781
0.9%
22893231
0.9%
22513691
0.9%
22364931
0.9%
22059771
0.9%
22059761
0.9%
21972851
0.9%
21895531
0.9%
21761341
0.9%
21692011
0.9%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1008.0 B
https://www.tvmaze.com/episodes/1988861/sim-for-you-4x23-chanyeols-episode-23
 
1
https://www.tvmaze.com/episodes/1985471/you-complete-me-1x15-episode-15
 
1
https://www.tvmaze.com/episodes/2000061/ultimate-note-1x14-episode-14
 
1
https://www.tvmaze.com/episodes/2000060/ultimate-note-1x13-episode-13
 
1
https://www.tvmaze.com/episodes/1997517/the-penalty-zone-1x10-episode-10
 
1
Other values (105)
105 

Length

Max length150
Median length104.5
Mean length81.85454545
Min length58

Characters and Unicode

Total characters9004
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1988861/sim-for-you-4x23-chanyeols-episode-23
2nd rowhttps://www.tvmaze.com/episodes/1977892/obycnaa-zensina-2x01-seria-10
3rd rowhttps://www.tvmaze.com/episodes/1977898/obycnaa-zensina-2x02-seria-11
4th rowhttps://www.tvmaze.com/episodes/1963998/257-pricin-ctoby-zit-2x08-seria-21
5th rowhttps://www.tvmaze.com/episodes/1949910/smesariki-novyj-sezon-1x31-emigrant-cast-1

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988861/sim-for-you-4x23-chanyeols-episode-231
 
0.9%
https://www.tvmaze.com/episodes/1985471/you-complete-me-1x15-episode-151
 
0.9%
https://www.tvmaze.com/episodes/2000061/ultimate-note-1x14-episode-141
 
0.9%
https://www.tvmaze.com/episodes/2000060/ultimate-note-1x13-episode-131
 
0.9%
https://www.tvmaze.com/episodes/1997517/the-penalty-zone-1x10-episode-101
 
0.9%
https://www.tvmaze.com/episodes/1997516/the-penalty-zone-1x09-episode-91
 
0.9%
https://www.tvmaze.com/episodes/1990901/nimra-etnin-1x08-hush-hush1
 
0.9%
https://www.tvmaze.com/episodes/1988403/love-teenager-1x01-i-kissed-my-handsome-guy-friend-at-school1
 
0.9%
https://www.tvmaze.com/episodes/1985698/schulz-saves-america-1x04-a-nation-divided-crybaby-cooper-and-tantruming-tucker-are-tearing-the-country-in-two1
 
0.9%
https://www.tvmaze.com/episodes/1985697/schulz-saves-america-1x03-black-lives-matter-protests-police-and-hollywood-hypocrites1
 
0.9%
Other values (100)100
90.9%

Length

2022-05-09T21:16:05.108081image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988861/sim-for-you-4x23-chanyeols-episode-231
 
0.9%
https://www.tvmaze.com/episodes/2169060/after-mom-falls-asleep-4x16-kai1
 
0.9%
https://www.tvmaze.com/episodes/1963998/257-pricin-ctoby-zit-2x08-seria-211
 
0.9%
https://www.tvmaze.com/episodes/1949910/smesariki-novyj-sezon-1x31-emigrant-cast-11
 
0.9%
https://www.tvmaze.com/episodes/1949911/smesariki-novyj-sezon-1x32-zag1
 
0.9%
https://www.tvmaze.com/episodes/1960728/psih-1x07-osoznanie1
 
0.9%
https://www.tvmaze.com/episodes/1982405/volk-1x07-seria-071
 
0.9%
https://www.tvmaze.com/episodes/1982406/volk-1x08-seria-081
 
0.9%
https://www.tvmaze.com/episodes/1988012/muzskaa-tema-1x01-seria-11
 
0.9%
https://www.tvmaze.com/episodes/1985787/theres-a-pit-in-my-senior-martial-brothers-brain-2x09-episode-91
 
0.9%
Other values (100)100
90.9%

Most occurring characters

ValueCountFrequency (%)
e755
 
8.4%
-711
 
7.9%
s590
 
6.6%
t564
 
6.3%
/550
 
6.1%
o452
 
5.0%
i366
 
4.1%
w365
 
4.1%
a363
 
4.0%
m340
 
3.8%
Other values (30)3948
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6139
68.2%
Decimal Number1274
 
14.1%
Other Punctuation880
 
9.8%
Dash Punctuation711
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e755
12.3%
s590
 
9.6%
t564
 
9.2%
o452
 
7.4%
i366
 
6.0%
w365
 
5.9%
a363
 
5.9%
m340
 
5.5%
p332
 
5.4%
d244
 
4.0%
Other values (16)1768
28.8%
Decimal Number
ValueCountFrequency (%)
1271
21.3%
0183
14.4%
2169
13.3%
9162
12.7%
792
 
7.2%
390
 
7.1%
888
 
6.9%
580
 
6.3%
676
 
6.0%
463
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/550
62.5%
.220
 
25.0%
:110
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-711
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6139
68.2%
Common2865
31.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e755
12.3%
s590
 
9.6%
t564
 
9.2%
o452
 
7.4%
i366
 
6.0%
w365
 
5.9%
a363
 
5.9%
m340
 
5.5%
p332
 
5.4%
d244
 
4.0%
Other values (16)1768
28.8%
Common
ValueCountFrequency (%)
-711
24.8%
/550
19.2%
1271
 
9.5%
.220
 
7.7%
0183
 
6.4%
2169
 
5.9%
9162
 
5.7%
:110
 
3.8%
792
 
3.2%
390
 
3.1%
Other values (4)307
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII9004
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e755
 
8.4%
-711
 
7.9%
s590
 
6.6%
t564
 
6.3%
/550
 
6.1%
o452
 
5.0%
i366
 
4.1%
w365
 
4.1%
a363
 
4.0%
m340
 
3.8%
Other values (30)3948
43.8%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct97
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size1008.0 B
Episode 9
 
3
Episode 3
 
3
Episode 5
 
3
Episode 26
 
2
Blippi Visits The Horse And Reindeer Farm | Animals For Kids
 
2
Other values (92)
97 

Length

Max length85
Median length59
Mean length20.17272727
Min length3

Characters and Unicode

Total characters2219
Distinct characters129
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)79.1%

Sample

1st rowChanyeol's Episode 23
2nd rowСерия 10
3rd rowСерия 11
4th rowСерия 21
5th rowЭмигрант. Часть 1

Common Values

ValueCountFrequency (%)
Episode 93
 
2.7%
Episode 33
 
2.7%
Episode 53
 
2.7%
Episode 262
 
1.8%
Blippi Visits The Horse And Reindeer Farm | Animals For Kids2
 
1.8%
Episode 192
 
1.8%
Episode 102
 
1.8%
Terra Firma, Part 22
 
1.8%
Episode 22
 
1.8%
2. Bölüm2
 
1.8%
Other values (87)87
79.1%

Length

2022-05-09T21:16:05.216477image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode33
 
8.4%
the16
 
4.1%
and12
 
3.0%
27
 
1.8%
серия6
 
1.5%
16
 
1.5%
35
 
1.3%
5
 
1.3%
bölüm4
 
1.0%
173
 
0.8%
Other values (255)297
75.4%

Most occurring characters

ValueCountFrequency (%)
284
 
12.8%
e157
 
7.1%
i122
 
5.5%
o111
 
5.0%
s104
 
4.7%
r94
 
4.2%
d84
 
3.8%
n84
 
3.8%
a83
 
3.7%
t64
 
2.9%
Other values (119)1032
46.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1457
65.7%
Uppercase Letter299
 
13.5%
Space Separator284
 
12.8%
Decimal Number113
 
5.1%
Other Punctuation43
 
1.9%
Other Letter10
 
0.5%
Dash Punctuation3
 
0.1%
Close Punctuation2
 
0.1%
Math Symbol2
 
0.1%
Initial Punctuation2
 
0.1%
Other values (2)4
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e157
 
10.8%
i122
 
8.4%
o111
 
7.6%
s104
 
7.1%
r94
 
6.5%
d84
 
5.8%
n84
 
5.8%
a83
 
5.7%
t64
 
4.4%
p54
 
3.7%
Other values (48)500
34.3%
Uppercase Letter
ValueCountFrequency (%)
E48
16.1%
T22
 
7.4%
H22
 
7.4%
P21
 
7.0%
A18
 
6.0%
C18
 
6.0%
M15
 
5.0%
S15
 
5.0%
F12
 
4.0%
O12
 
4.0%
Other values (26)96
32.1%
Decimal Number
ValueCountFrequency (%)
126
23.0%
225
22.1%
016
14.2%
310
 
8.8%
99
 
8.0%
58
 
7.1%
68
 
7.1%
75
 
4.4%
43
 
2.7%
83
 
2.7%
Other Punctuation
ValueCountFrequency (%)
:14
32.6%
.8
18.6%
,8
18.6%
'5
 
11.6%
#2
 
4.7%
"2
 
4.7%
!2
 
4.7%
?1
 
2.3%
&1
 
2.3%
Other Letter
ValueCountFrequency (%)
م2
20.0%
ي1
10.0%
د1
10.0%
أ1
10.0%
ر1
10.0%
ا1
10.0%
ض1
10.0%
ف1
10.0%
ة1
10.0%
Space Separator
ValueCountFrequency (%)
284
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%
Initial Punctuation
ValueCountFrequency (%)
«2
100.0%
Final Punctuation
ValueCountFrequency (%)
»2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1522
68.6%
Common453
 
20.4%
Cyrillic234
 
10.5%
Arabic10
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e157
 
10.3%
i122
 
8.0%
o111
 
7.3%
s104
 
6.8%
r94
 
6.2%
d84
 
5.5%
n84
 
5.5%
a83
 
5.5%
t64
 
4.2%
p54
 
3.5%
Other values (45)565
37.1%
Cyrillic
ValueCountFrequency (%)
и26
 
11.1%
е23
 
9.8%
р15
 
6.4%
т15
 
6.4%
с15
 
6.4%
а14
 
6.0%
н13
 
5.6%
я10
 
4.3%
о9
 
3.8%
л8
 
3.4%
Other values (29)86
36.8%
Common
ValueCountFrequency (%)
284
62.7%
126
 
5.7%
225
 
5.5%
016
 
3.5%
:14
 
3.1%
310
 
2.2%
99
 
2.0%
.8
 
1.8%
58
 
1.8%
,8
 
1.8%
Other values (16)45
 
9.9%
Arabic
ValueCountFrequency (%)
م2
20.0%
ي1
10.0%
د1
10.0%
أ1
10.0%
ر1
10.0%
ا1
10.0%
ض1
10.0%
ف1
10.0%
ة1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1959
88.3%
Cyrillic234
 
10.5%
None16
 
0.7%
Arabic10
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
284
 
14.5%
e157
 
8.0%
i122
 
6.2%
o111
 
5.7%
s104
 
5.3%
r94
 
4.8%
d84
 
4.3%
n84
 
4.3%
a83
 
4.2%
t64
 
3.3%
Other values (63)772
39.4%
Cyrillic
ValueCountFrequency (%)
и26
 
11.1%
е23
 
9.8%
р15
 
6.4%
т15
 
6.4%
с15
 
6.4%
а14
 
6.0%
н13
 
5.6%
я10
 
4.3%
о9
 
3.8%
л8
 
3.4%
Other values (29)86
36.8%
None
ValueCountFrequency (%)
ö4
25.0%
ü4
25.0%
«2
12.5%
»2
12.5%
ä1
 
6.2%
å1
 
6.2%
ã1
 
6.2%
ó1
 
6.2%
Arabic
ValueCountFrequency (%)
م2
20.0%
ي1
10.0%
د1
10.0%
أ1
10.0%
ر1
10.0%
ا1
10.0%
ض1
10.0%
ف1
10.0%
ة1
10.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct15
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.0545455
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1008.0 B
2022-05-09T21:16:05.444481image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)2

Descriptive statistics

Standard deviation555.3892236
Coefficient of variation (CV)3.304815244
Kurtosis7.708986622
Mean168.0545455
Median Absolute Deviation (MAD)0
Skewness3.093149918
Sum18486
Variance308457.1897
MonotonicityNot monotonic
2022-05-09T21:16:05.546360image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
163
57.3%
215
 
13.6%
20209
 
8.2%
37
 
6.4%
45
 
4.5%
52
 
1.8%
101
 
0.9%
81
 
0.9%
131
 
0.9%
181
 
0.9%
Other values (5)5
 
4.5%
ValueCountFrequency (%)
163
57.3%
215
 
13.6%
37
 
6.4%
45
 
4.5%
52
 
1.8%
71
 
0.9%
81
 
0.9%
91
 
0.9%
101
 
0.9%
131
 
0.9%
ValueCountFrequency (%)
20209
8.2%
511
 
0.9%
311
 
0.9%
181
 
0.9%
151
 
0.9%
131
 
0.9%
101
 
0.9%
91
 
0.9%
81
 
0.9%
71
 
0.9%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)40.2%
Missing3
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean25.94392523
Minimum1
Maximum344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1008.0 B
2022-05-09T21:16:05.676466image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median9
Q321.5
95-th percentile97.3
Maximum344
Range343
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation55.92259336
Coefficient of variation (CV)2.155517828
Kurtosis20.61319166
Mean25.94392523
Median Absolute Deviation (MAD)7
Skewness4.397568889
Sum2776
Variance3127.336449
MonotonicityNot monotonic
2022-05-09T21:16:05.788332image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
210
 
9.1%
19
 
8.2%
77
 
6.4%
36
 
5.5%
66
 
5.5%
106
 
5.5%
55
 
4.5%
85
 
4.5%
95
 
4.5%
44
 
3.6%
Other values (33)44
40.0%
ValueCountFrequency (%)
19
8.2%
210
9.1%
36
5.5%
44
 
3.6%
55
4.5%
66
5.5%
77
6.4%
85
4.5%
95
4.5%
106
5.5%
ValueCountFrequency (%)
3441
0.9%
3081
0.9%
3071
0.9%
1541
0.9%
1201
0.9%
1031
0.9%
841
0.9%
681
0.9%
641
0.9%
581
0.9%

type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1008.0 B
regular
107 
insignificant_special
 
3

Length

Max length21
Median length7
Mean length7.381818182
Min length7

Characters and Unicode

Total characters812
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular107
97.3%
insignificant_special3
 
2.7%

Length

2022-05-09T21:16:05.883848image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:05.979700image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular107
97.3%
insignificant_special3
 
2.7%

Most occurring characters

ValueCountFrequency (%)
r214
26.4%
a113
13.9%
e110
13.5%
g110
13.5%
l110
13.5%
u107
13.2%
i15
 
1.8%
n9
 
1.1%
s6
 
0.7%
c6
 
0.7%
Other values (4)12
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter809
99.6%
Connector Punctuation3
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r214
26.5%
a113
14.0%
e110
13.6%
g110
13.6%
l110
13.6%
u107
13.2%
i15
 
1.9%
n9
 
1.1%
s6
 
0.7%
c6
 
0.7%
Other values (3)9
 
1.1%
Connector Punctuation
ValueCountFrequency (%)
_3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin809
99.6%
Common3
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
r214
26.5%
a113
14.0%
e110
13.6%
g110
13.6%
l110
13.6%
u107
13.2%
i15
 
1.9%
n9
 
1.1%
s6
 
0.7%
c6
 
0.7%
Other values (3)9
 
1.1%
Common
ValueCountFrequency (%)
_3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII812
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r214
26.4%
a113
13.9%
e110
13.5%
g110
13.5%
l110
13.5%
u107
13.2%
i15
 
1.8%
n9
 
1.1%
s6
 
0.7%
c6
 
0.7%
Other values (4)12
 
1.5%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1008.0 B
2020-12-17
110 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1100
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-17
2nd row2020-12-17
3rd row2020-12-17
4th row2020-12-17
5th row2020-12-17

Common Values

ValueCountFrequency (%)
2020-12-17110
100.0%

Length

2022-05-09T21:16:06.044654image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:06.141787image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-17110
100.0%

Most occurring characters

ValueCountFrequency (%)
2330
30.0%
0220
20.0%
-220
20.0%
1220
20.0%
7110
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number880
80.0%
Dash Punctuation220
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2330
37.5%
0220
25.0%
1220
25.0%
7110
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-220
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2330
30.0%
0220
20.0%
-220
20.0%
1220
20.0%
7110
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2330
30.0%
0220
20.0%
-220
20.0%
1220
20.0%
7110
 
10.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size1008.0 B
nan
81 
20:00
 
6
12:00
 
5
10:00
 
3
06:00
 
2
Other values (11)
13 

Length

Max length5
Median length3
Mean length3.527272727
Min length3

Characters and Unicode

Total characters388
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)8.2%

Sample

1st row06:00
2nd row10:00
3rd row10:00
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan81
73.6%
20:006
 
5.5%
12:005
 
4.5%
10:003
 
2.7%
06:002
 
1.8%
21:002
 
1.8%
22:002
 
1.8%
11:001
 
0.9%
17:351
 
0.9%
17:001
 
0.9%
Other values (6)6
 
5.5%

Length

2022-05-09T21:16:06.226392image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan81
73.6%
20:006
 
5.5%
12:005
 
4.5%
10:003
 
2.7%
06:002
 
1.8%
21:002
 
1.8%
22:002
 
1.8%
11:001
 
0.9%
17:351
 
0.9%
17:001
 
0.9%
Other values (6)6
 
5.5%

Most occurring characters

ValueCountFrequency (%)
n162
41.8%
a81
20.9%
066
17.0%
:29
 
7.5%
220
 
5.2%
118
 
4.6%
53
 
0.8%
93
 
0.8%
62
 
0.5%
72
 
0.5%
Other values (2)2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter243
62.6%
Decimal Number116
29.9%
Other Punctuation29
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
066
56.9%
220
 
17.2%
118
 
15.5%
53
 
2.6%
93
 
2.6%
62
 
1.7%
72
 
1.7%
31
 
0.9%
81
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
n162
66.7%
a81
33.3%
Other Punctuation
ValueCountFrequency (%)
:29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin243
62.6%
Common145
37.4%

Most frequent character per script

Common
ValueCountFrequency (%)
066
45.5%
:29
20.0%
220
 
13.8%
118
 
12.4%
53
 
2.1%
93
 
2.1%
62
 
1.4%
72
 
1.4%
31
 
0.7%
81
 
0.7%
Latin
ValueCountFrequency (%)
n162
66.7%
a81
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n162
41.8%
a81
20.9%
066
17.0%
:29
 
7.5%
220
 
5.2%
118
 
4.6%
53
 
0.8%
93
 
0.8%
62
 
0.5%
72
 
0.5%
Other values (2)2
 
0.5%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct22
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size1008.0 B
2020-12-17T12:00:00+00:00
41 
2020-12-17T04:00:00+00:00
13 
2020-12-17T17:00:00+00:00
10 
2020-12-17T00:00:00+00:00
2020-12-17T11:00:00+00:00
Other values (17)
32 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2750
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)7.3%

Sample

1st row2020-12-16T21:00:00+00:00
2nd row2020-12-16T22:00:00+00:00
3rd row2020-12-16T22:00:00+00:00
4th row2020-12-17T00:00:00+00:00
5th row2020-12-17T00:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-17T12:00:00+00:0041
37.3%
2020-12-17T04:00:00+00:0013
 
11.8%
2020-12-17T17:00:00+00:0010
 
9.1%
2020-12-17T00:00:00+00:007
 
6.4%
2020-12-17T11:00:00+00:007
 
6.4%
2020-12-17T09:00:00+00:005
 
4.5%
2020-12-17T03:00:00+00:004
 
3.6%
2020-12-17T14:00:00+00:003
 
2.7%
2020-12-17T10:00:00+00:002
 
1.8%
2020-12-16T22:00:00+00:002
 
1.8%
Other values (12)16
 
14.5%

Length

2022-05-09T21:16:06.318212image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-17t12:00:00+00:0041
37.3%
2020-12-17t04:00:00+00:0013
 
11.8%
2020-12-17t17:00:00+00:0010
 
9.1%
2020-12-17t00:00:00+00:007
 
6.4%
2020-12-17t11:00:00+00:007
 
6.4%
2020-12-17t09:00:00+00:005
 
4.5%
2020-12-17t03:00:00+00:004
 
3.6%
2020-12-17t14:00:00+00:003
 
2.7%
2020-12-17t05:00:00+00:002
 
1.8%
2020-12-17t08:00:00+00:002
 
1.8%
Other values (12)16
 
14.5%

Most occurring characters

ValueCountFrequency (%)
01143
41.6%
2379
 
13.8%
:330
 
12.0%
1296
 
10.8%
-220
 
8.0%
7116
 
4.2%
T110
 
4.0%
+110
 
4.0%
416
 
0.6%
39
 
0.3%
Other values (4)21
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1980
72.0%
Other Punctuation330
 
12.0%
Dash Punctuation220
 
8.0%
Uppercase Letter110
 
4.0%
Math Symbol110
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01143
57.7%
2379
 
19.1%
1296
 
14.9%
7116
 
5.9%
416
 
0.8%
39
 
0.5%
96
 
0.3%
86
 
0.3%
56
 
0.3%
63
 
0.2%
Other Punctuation
ValueCountFrequency (%)
:330
100.0%
Dash Punctuation
ValueCountFrequency (%)
-220
100.0%
Uppercase Letter
ValueCountFrequency (%)
T110
100.0%
Math Symbol
ValueCountFrequency (%)
+110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2640
96.0%
Latin110
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01143
43.3%
2379
 
14.4%
:330
 
12.5%
1296
 
11.2%
-220
 
8.3%
7116
 
4.4%
+110
 
4.2%
416
 
0.6%
39
 
0.3%
96
 
0.2%
Other values (3)15
 
0.6%
Latin
ValueCountFrequency (%)
T110
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01143
41.6%
2379
 
13.8%
:330
 
12.0%
1296
 
10.8%
-220
 
8.0%
7116
 
4.2%
T110
 
4.0%
+110
 
4.0%
416
 
0.6%
39
 
0.3%
Other values (4)21
 
0.8%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct35
Distinct (%)35.0%
Missing10
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean38.95
Minimum6
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1008.0 B
2022-05-09T21:16:06.429139image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile7.95
Q118
median41
Q345
95-th percentile73.85
Maximum240
Range234
Interquartile range (IQR)27

Descriptive statistics

Standard deviation30.4290448
Coefficient of variation (CV)0.7812334995
Kurtosis19.2943411
Mean38.95
Median Absolute Deviation (MAD)16
Skewness3.448321864
Sum3895
Variance925.9267677
MonotonicityNot monotonic
2022-05-09T21:16:06.547163image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
4522
20.0%
207
 
6.4%
307
 
6.4%
606
 
5.5%
125
 
4.5%
185
 
4.5%
424
 
3.6%
73
 
2.7%
1203
 
2.7%
173
 
2.7%
Other values (25)35
31.8%
(Missing)10
 
9.1%
ValueCountFrequency (%)
62
 
1.8%
73
2.7%
82
 
1.8%
101
 
0.9%
125
4.5%
131
 
0.9%
153
2.7%
161
 
0.9%
173
2.7%
185
4.5%
ValueCountFrequency (%)
2401
 
0.9%
1203
2.7%
901
 
0.9%
731
 
0.9%
611
 
0.9%
606
5.5%
591
 
0.9%
541
 
0.9%
531
 
0.9%
513
2.7%

image
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct32
Distinct (%)100.0%
Missing78
Missing (%)70.9%
Memory size1008.0 B
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/341/854100.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/341/854100.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/720705.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/720705.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/732257.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/732257.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/363/908141.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/363/908141.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726711.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726711.jpg'}
 
1
Other values (27)
27 

Length

Max length178
Median length176
Mean length176.0625
Min length176

Characters and Unicode

Total characters5634
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723163.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723163.jpg'}
2nd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723164.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723164.jpg'}
3rd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/301/752692.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/301/752692.jpg'}
4th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/294/737157.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/294/737157.jpg'}
5th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723252.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723252.jpg'}

Common Values

ValueCountFrequency (%)
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/341/854100.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/341/854100.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/720705.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/720705.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/732257.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/732257.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/363/908141.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/363/908141.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726711.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726711.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/731964.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/731964.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723341.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723341.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/377/944452.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/377/944452.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726728.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726728.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726727.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726727.jpg'}1
 
0.9%
Other values (22)22
 
20.0%
(Missing)78
70.9%

Length

2022-05-09T21:16:06.660205image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
medium32
25.0%
original32
25.0%
https://static.tvmaze.com/uploads/images/medium_landscape/289/723198.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721856.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/288/720566.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720566.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/407/1018513.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/medium_landscape/407/1018513.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/723198.jpg1
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/723167.jpg1
 
0.8%
Other values (56)56
43.8%

Most occurring characters

ValueCountFrequency (%)
/448
 
8.0%
a384
 
6.8%
t352
 
6.2%
m320
 
5.7%
i320
 
5.7%
s288
 
5.1%
e256
 
4.5%
'256
 
4.5%
o224
 
4.0%
p224
 
4.0%
Other values (28)2562
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3776
67.0%
Other Punctuation1056
 
18.7%
Decimal Number578
 
10.3%
Space Separator96
 
1.7%
Connector Punctuation64
 
1.1%
Close Punctuation32
 
0.6%
Open Punctuation32
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a384
 
10.2%
t352
 
9.3%
m320
 
8.5%
i320
 
8.5%
s288
 
7.6%
e256
 
6.8%
o224
 
5.9%
p224
 
5.9%
g192
 
5.1%
c192
 
5.1%
Other values (9)1024
27.1%
Decimal Number
ValueCountFrequency (%)
2120
20.8%
788
15.2%
960
10.4%
358
10.0%
858
10.0%
146
 
8.0%
046
 
8.0%
640
 
6.9%
432
 
5.5%
530
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/448
42.4%
'256
24.2%
.192
18.2%
:128
 
12.1%
,32
 
3.0%
Space Separator
ValueCountFrequency (%)
96
100.0%
Connector Punctuation
ValueCountFrequency (%)
_64
100.0%
Close Punctuation
ValueCountFrequency (%)
}32
100.0%
Open Punctuation
ValueCountFrequency (%)
{32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3776
67.0%
Common1858
33.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/448
24.1%
'256
13.8%
.192
10.3%
:128
 
6.9%
2120
 
6.5%
96
 
5.2%
788
 
4.7%
_64
 
3.4%
960
 
3.2%
358
 
3.1%
Other values (9)348
18.7%
Latin
ValueCountFrequency (%)
a384
 
10.2%
t352
 
9.3%
m320
 
8.5%
i320
 
8.5%
s288
 
7.6%
e256
 
6.8%
o224
 
5.9%
p224
 
5.9%
g192
 
5.1%
c192
 
5.1%
Other values (9)1024
27.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII5634
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/448
 
8.0%
a384
 
6.8%
t352
 
6.2%
m320
 
5.7%
i320
 
5.7%
s288
 
5.1%
e256
 
4.5%
'256
 
4.5%
o224
 
4.0%
p224
 
4.0%
Other values (28)2562
45.5%

summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct26
Distinct (%)23.6%
Missing0
Missing (%)0.0%
Memory size1008.0 B
nan
85 
<p><b>#Scared Meㅇㅍㅇ #Under The Sea♬ #The Last Supper</b></p>
 
1
<p>Jason goes on a date with a woman who is forced to bring her young son along, and it's clear he has no home training. The date quickly goes bad and leads him back to Carmen. Bryan deals with the fallout of his relationship much to the crew's dismay. Lacy gets the call for a new opportunity. Carmen makes herself comfortable in Jason's life.</p>
 
1
<p>AJ starts exuding some odd behavior as he protests to go back to Baltimore. Mounting inconsistencies emerge about Corey that leaves Sam in doubt.</p>
 
1
<p>Perhaps the biggest rivalry in six-man football, the Greyhounds take on their cross-town rival, the Gordon Longhorns with all of Strawn watching.</p>
 
1
Other values (21)
21 

Length

Max length498
Median length3
Mean length54.46363636
Min length3

Characters and Unicode

Total characters5991
Distinct characters74
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)22.7%

Sample

1st row<p><b>#Scared Meㅇㅍㅇ #Under The Sea♬ #The Last Supper</b></p>
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan85
77.3%
<p><b>#Scared Meㅇㅍㅇ #Under The Sea♬ #The Last Supper</b></p>1
 
0.9%
<p>Jason goes on a date with a woman who is forced to bring her young son along, and it's clear he has no home training. The date quickly goes bad and leads him back to Carmen. Bryan deals with the fallout of his relationship much to the crew's dismay. Lacy gets the call for a new opportunity. Carmen makes herself comfortable in Jason's life.</p>1
 
0.9%
<p>AJ starts exuding some odd behavior as he protests to go back to Baltimore. Mounting inconsistencies emerge about Corey that leaves Sam in doubt.</p>1
 
0.9%
<p>Perhaps the biggest rivalry in six-man football, the Greyhounds take on their cross-town rival, the Gordon Longhorns with all of Strawn watching.</p>1
 
0.9%
<p>Cynthia is in disbelief as she has finally caught Malcolm and Sarah in their long-standing affair. Ruth shares troubling news with Oliver about what really happens when the girls leave with Lilo. The Highest and River's relationship grows as Dikahn's dislike for River grows. </p>1
 
0.9%
<p>Hosted by D.J. "Shangela" Pierce (HBO's "We're Here," "RuPaul's Drag Race," "A Star Is Born"), this reunion special is a chance for Chad, Faith, Garrett and their love interests to unwrap everything that's gone down since last Christmas - from settling scores and revealing juicy behind-the-scenes stories to unmasking secret hookups and answering whether our couples stayed together... or said goodbye. With her trademark flair, humor and insight, Shangela stokes the Yule log fire.</p>1
 
0.9%
<p>It's Alive with Brad Leone is back for episode 77 and this time Brad is learning all about oyster reefs. Join Brad in New York Harbor as he learns how oyster shells are put to work after restaurants dispose of them. New York Harbor used to have 220,000 acres of oyster reefs, but it only took 100 years to harvest them all once Europeans arrived. That's where Billion Oyster Project comes in -- recreating New York's lost oyster fields. And Brad's here to help.</p>1
 
0.9%
<p>Oscar, Hedgehog and Puddle must figure out what's wrong with the King when he orders the aliens to turn all the planet's</p>1
 
0.9%
<p>Hedgehog and Oscar discover alien jesters who live under the floorboards of the castle.</p>1
 
0.9%
Other values (16)16
 
14.5%

Length

2022-05-09T21:16:06.798381image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan85
 
8.3%
the55
 
5.3%
and34
 
3.3%
to33
 
3.2%
of17
 
1.7%
on14
 
1.4%
her13
 
1.3%
a13
 
1.3%
with13
 
1.3%
in12
 
1.2%
Other values (560)741
71.9%

Most occurring characters

ValueCountFrequency (%)
918
15.3%
e541
 
9.0%
n468
 
7.8%
a422
 
7.0%
t359
 
6.0%
o328
 
5.5%
r310
 
5.2%
s298
 
5.0%
i277
 
4.6%
h261
 
4.4%
Other values (64)1809
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4512
75.3%
Space Separator921
 
15.4%
Uppercase Letter237
 
4.0%
Other Punctuation175
 
2.9%
Math Symbol112
 
1.9%
Decimal Number13
 
0.2%
Dash Punctuation11
 
0.2%
Close Punctuation3
 
0.1%
Open Punctuation3
 
0.1%
Other Letter3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e541
12.0%
n468
10.4%
a422
 
9.4%
t359
 
8.0%
o328
 
7.3%
r310
 
6.9%
s298
 
6.6%
i277
 
6.1%
h261
 
5.8%
l179
 
4.0%
Other values (16)1069
23.7%
Uppercase Letter
ValueCountFrequency (%)
S21
 
8.9%
T21
 
8.9%
M18
 
7.6%
A15
 
6.3%
B15
 
6.3%
C14
 
5.9%
H13
 
5.5%
J12
 
5.1%
W11
 
4.6%
L9
 
3.8%
Other values (13)88
37.1%
Other Punctuation
ValueCountFrequency (%)
.57
32.6%
,44
25.1%
/28
16.0%
'27
15.4%
"10
 
5.7%
:3
 
1.7%
#3
 
1.7%
?1
 
0.6%
!1
 
0.6%
%1
 
0.6%
Decimal Number
ValueCountFrequency (%)
06
46.2%
92
 
15.4%
22
 
15.4%
72
 
15.4%
11
 
7.7%
Space Separator
ValueCountFrequency (%)
918
99.7%
 3
 
0.3%
Math Symbol
ValueCountFrequency (%)
<56
50.0%
>56
50.0%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Dash Punctuation
ValueCountFrequency (%)
-11
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4749
79.3%
Common1239
 
20.7%
Hangul3
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e541
11.4%
n468
 
9.9%
a422
 
8.9%
t359
 
7.6%
o328
 
6.9%
r310
 
6.5%
s298
 
6.3%
i277
 
5.8%
h261
 
5.5%
l179
 
3.8%
Other values (39)1306
27.5%
Common
ValueCountFrequency (%)
918
74.1%
.57
 
4.6%
<56
 
4.5%
>56
 
4.5%
,44
 
3.6%
/28
 
2.3%
'27
 
2.2%
-11
 
0.9%
"10
 
0.8%
06
 
0.5%
Other values (13)26
 
2.1%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII5984
99.9%
None3
 
0.1%
Compat Jamo3
 
0.1%
Misc Symbols1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
918
15.3%
e541
 
9.0%
n468
 
7.8%
a422
 
7.1%
t359
 
6.0%
o328
 
5.5%
r310
 
5.2%
s298
 
5.0%
i277
 
4.6%
h261
 
4.4%
Other values (60)1802
30.1%
None
ValueCountFrequency (%)
 3
100.0%
Compat Jamo
ValueCountFrequency (%)
2
66.7%
1
33.3%
Misc Symbols
ValueCountFrequency (%)
1
100.0%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct84
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45508.27273
Minimum2504
Maximum60848
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1008.0 B
2022-05-09T21:16:06.913522image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2504
5-th percentile15886.75
Q141946.75
median50916
Q352780
95-th percentile58002.05
Maximum60848
Range58344
Interquartile range (IQR)10833.25

Descriptive statistics

Standard deviation12811.4031
Coefficient of variation (CV)0.2815181137
Kurtosis2.100194084
Mean45508.27273
Median Absolute Deviation (MAD)2959
Skewness-1.660858619
Sum5005910
Variance164132049.3
MonotonicityNot monotonic
2022-05-09T21:16:07.028992image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
526184
 
3.6%
524354
 
3.6%
266433
 
2.7%
498433
 
2.7%
547622
 
1.8%
479122
 
1.8%
528062
 
1.8%
527432
 
1.8%
586892
 
1.8%
527992
 
1.8%
Other values (74)84
76.4%
ValueCountFrequency (%)
25041
0.9%
65441
0.9%
74801
0.9%
132151
0.9%
152502
1.8%
166651
0.9%
167531
0.9%
170461
0.9%
170781
0.9%
262681
0.9%
ValueCountFrequency (%)
608482
1.8%
598531
0.9%
586892
1.8%
583671
0.9%
575561
0.9%
573851
0.9%
568481
0.9%
566051
0.9%
562531
0.9%
547622
1.8%

_embedded_show_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct84
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size1008.0 B
https://www.tvmaze.com/shows/52618/unter-freunden-stirbt-man-nicht
 
4
https://www.tvmaze.com/shows/52435/schulz-saves-america
 
4
https://www.tvmaze.com/shows/26643/summer-camp-island
 
3
https://www.tvmaze.com/shows/49843/aile-sirketi
 
3
https://www.tvmaze.com/shows/54762/youths-in-the-breeze
 
2
Other values (79)
94 

Length

Max length83
Median length57
Mean length50.50909091
Min length39

Characters and Unicode

Total characters5556
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)58.2%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/39115/obycnaa-zensina
3rd rowhttps://www.tvmaze.com/shows/39115/obycnaa-zensina
4th rowhttps://www.tvmaze.com/shows/43722/257-pricin-ctoby-zit
5th rowhttps://www.tvmaze.com/shows/48151/smesariki-novyj-sezon

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52618/unter-freunden-stirbt-man-nicht4
 
3.6%
https://www.tvmaze.com/shows/52435/schulz-saves-america4
 
3.6%
https://www.tvmaze.com/shows/26643/summer-camp-island3
 
2.7%
https://www.tvmaze.com/shows/49843/aile-sirketi3
 
2.7%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
1.8%
https://www.tvmaze.com/shows/47912/the-wolf2
 
1.8%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
1.8%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
1.8%
https://www.tvmaze.com/shows/58689/my-supernatural-power2
 
1.8%
https://www.tvmaze.com/shows/52799/futmallscom2
 
1.8%
Other values (74)84
76.4%

Length

2022-05-09T21:16:07.154752image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52618/unter-freunden-stirbt-man-nicht4
 
3.6%
https://www.tvmaze.com/shows/52435/schulz-saves-america4
 
3.6%
https://www.tvmaze.com/shows/26643/summer-camp-island3
 
2.7%
https://www.tvmaze.com/shows/49843/aile-sirketi3
 
2.7%
https://www.tvmaze.com/shows/53830/witches2
 
1.8%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
1.8%
https://www.tvmaze.com/shows/60848/blippi2
 
1.8%
https://www.tvmaze.com/shows/52780/mermaid-prince2
 
1.8%
https://www.tvmaze.com/shows/52181/volk2
 
1.8%
https://www.tvmaze.com/shows/52105/be-with-you2
 
1.8%
Other values (74)84
76.4%

Most occurring characters

ValueCountFrequency (%)
/550
 
9.9%
w463
 
8.3%
t460
 
8.3%
s443
 
8.0%
o314
 
5.7%
e303
 
5.5%
m285
 
5.1%
h280
 
5.0%
a227
 
4.1%
.220
 
4.0%
Other values (29)2011
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3928
70.7%
Other Punctuation880
 
15.8%
Decimal Number558
 
10.0%
Dash Punctuation190
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w463
11.8%
t460
11.7%
s443
11.3%
o314
 
8.0%
e303
 
7.7%
m285
 
7.3%
h280
 
7.1%
a227
 
5.8%
c160
 
4.1%
p140
 
3.6%
Other values (15)853
21.7%
Decimal Number
ValueCountFrequency (%)
596
17.2%
468
12.2%
267
12.0%
855
9.9%
655
9.9%
153
9.5%
349
8.8%
049
8.8%
735
 
6.3%
931
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/550
62.5%
.220
 
25.0%
:110
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3928
70.7%
Common1628
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w463
11.8%
t460
11.7%
s443
11.3%
o314
 
8.0%
e303
 
7.7%
m285
 
7.3%
h280
 
7.1%
a227
 
5.8%
c160
 
4.1%
p140
 
3.6%
Other values (15)853
21.7%
Common
ValueCountFrequency (%)
/550
33.8%
.220
 
13.5%
-190
 
11.7%
:110
 
6.8%
596
 
5.9%
468
 
4.2%
267
 
4.1%
855
 
3.4%
655
 
3.4%
153
 
3.3%
Other values (4)164
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII5556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/550
 
9.9%
w463
 
8.3%
t460
 
8.3%
s443
 
8.0%
o314
 
5.7%
e303
 
5.5%
m285
 
5.1%
h280
 
5.0%
a227
 
4.1%
.220
 
4.0%
Other values (29)2011
36.2%

_embedded_show_name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct84
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size1008.0 B
Unter Freunden stirbt man nicht
 
4
Schulz Saves America
 
4
Summer Camp Island
 
3
Aile Şirketi
 
3
Youths in the Breeze
 
2
Other values (79)
94 

Length

Max length50
Median length23
Mean length15.8
Min length4

Characters and Unicode

Total characters1738
Distinct characters105
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)58.2%

Sample

1st rowSim for You
2nd rowОбычная женщина
3rd rowОбычная женщина
4th row257 причин, чтобы жить
5th rowСмешарики. Новый сезон

Common Values

ValueCountFrequency (%)
Unter Freunden stirbt man nicht4
 
3.6%
Schulz Saves America4
 
3.6%
Summer Camp Island3
 
2.7%
Aile Şirketi3
 
2.7%
Youths in the Breeze2
 
1.8%
The Wolf2
 
1.8%
Ultimate Note2
 
1.8%
The Penalty Zone2
 
1.8%
My Supernatural Power2
 
1.8%
Futmalls.com2
 
1.8%
Other values (74)84
76.4%

Length

2022-05-09T21:16:07.265320image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the19
 
6.3%
you5
 
1.7%
unter4
 
1.3%
america4
 
1.3%
love4
 
1.3%
my4
 
1.3%
island4
 
1.3%
freunden4
 
1.3%
nicht4
 
1.3%
schulz4
 
1.3%
Other values (186)246
81.5%

Most occurring characters

ValueCountFrequency (%)
192
 
11.0%
e175
 
10.1%
r96
 
5.5%
t93
 
5.4%
a85
 
4.9%
i82
 
4.7%
n80
 
4.6%
o77
 
4.4%
s63
 
3.6%
h53
 
3.0%
Other values (95)742
42.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1245
71.6%
Uppercase Letter264
 
15.2%
Space Separator192
 
11.0%
Other Punctuation26
 
1.5%
Decimal Number11
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e175
14.1%
r96
 
7.7%
t93
 
7.5%
a85
 
6.8%
i82
 
6.6%
n80
 
6.4%
o77
 
6.2%
s63
 
5.1%
h53
 
4.3%
l52
 
4.2%
Other values (46)389
31.2%
Uppercase Letter
ValueCountFrequency (%)
S34
 
12.9%
T32
 
12.1%
M20
 
7.6%
B17
 
6.4%
A15
 
5.7%
W14
 
5.3%
C13
 
4.9%
F11
 
4.2%
Y10
 
3.8%
R9
 
3.4%
Other values (25)89
33.7%
Other Punctuation
ValueCountFrequency (%)
'6
23.1%
.6
23.1%
:5
19.2%
!4
15.4%
,2
 
7.7%
&2
 
7.7%
?1
 
3.8%
Decimal Number
ValueCountFrequency (%)
25
45.5%
02
 
18.2%
71
 
9.1%
51
 
9.1%
11
 
9.1%
61
 
9.1%
Space Separator
ValueCountFrequency (%)
192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1363
78.4%
Common229
 
13.2%
Cyrillic146
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e175
 
12.8%
r96
 
7.0%
t93
 
6.8%
a85
 
6.2%
i82
 
6.0%
n80
 
5.9%
o77
 
5.6%
s63
 
4.6%
h53
 
3.9%
l52
 
3.8%
Other values (45)507
37.2%
Cyrillic
ValueCountFrequency (%)
н13
 
8.9%
е13
 
8.9%
а12
 
8.2%
и11
 
7.5%
о11
 
7.5%
к8
 
5.5%
ч5
 
3.4%
я5
 
3.4%
т5
 
3.4%
ы5
 
3.4%
Other values (26)58
39.7%
Common
ValueCountFrequency (%)
192
83.8%
'6
 
2.6%
.6
 
2.6%
25
 
2.2%
:5
 
2.2%
!4
 
1.7%
,2
 
0.9%
02
 
0.9%
&2
 
0.9%
71
 
0.4%
Other values (4)4
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1584
91.1%
Cyrillic146
 
8.4%
None8
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
192
 
12.1%
e175
 
11.0%
r96
 
6.1%
t93
 
5.9%
a85
 
5.4%
i82
 
5.2%
n80
 
5.1%
o77
 
4.9%
s63
 
4.0%
h53
 
3.3%
Other values (54)588
37.1%
Cyrillic
ValueCountFrequency (%)
н13
 
8.9%
е13
 
8.9%
а12
 
8.2%
и11
 
7.5%
о11
 
7.5%
к8
 
5.5%
ч5
 
3.4%
я5
 
3.4%
т5
 
3.4%
ы5
 
3.4%
Other values (26)58
39.7%
None
ValueCountFrequency (%)
Ş3
37.5%
ı2
25.0%
ø1
 
12.5%
Ç1
 
12.5%
ğ1
 
12.5%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size1008.0 B
Scripted
64 
Talk Show
15 
Animation
10 
Reality
Variety
 
4
Other values (4)

Length

Max length11
Median length8
Mean length8.090909091
Min length4

Characters and Unicode

Total characters890
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rowReality
2nd rowScripted
3rd rowScripted
4th rowScripted
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted64
58.2%
Talk Show15
 
13.6%
Animation10
 
9.1%
Reality9
 
8.2%
Variety4
 
3.6%
Documentary3
 
2.7%
News2
 
1.8%
Sports2
 
1.8%
Game Show1
 
0.9%

Length

2022-05-09T21:16:07.370018image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:07.626175image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted64
50.8%
show16
 
12.7%
talk15
 
11.9%
animation10
 
7.9%
reality9
 
7.1%
variety4
 
3.2%
documentary3
 
2.4%
news2
 
1.6%
sports2
 
1.6%
game1
 
0.8%

Most occurring characters

ValueCountFrequency (%)
i97
10.9%
t92
10.3%
e83
9.3%
S82
9.2%
r73
 
8.2%
c67
 
7.5%
p66
 
7.4%
d64
 
7.2%
a42
 
4.7%
o31
 
3.5%
Other values (17)193
21.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter748
84.0%
Uppercase Letter126
 
14.2%
Space Separator16
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i97
13.0%
t92
12.3%
e83
11.1%
r73
9.8%
c67
9.0%
p66
8.8%
d64
8.6%
a42
 
5.6%
o31
 
4.1%
l24
 
3.2%
Other values (8)109
14.6%
Uppercase Letter
ValueCountFrequency (%)
S82
65.1%
T15
 
11.9%
A10
 
7.9%
R9
 
7.1%
V4
 
3.2%
D3
 
2.4%
N2
 
1.6%
G1
 
0.8%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin874
98.2%
Common16
 
1.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
i97
11.1%
t92
10.5%
e83
9.5%
S82
9.4%
r73
8.4%
c67
 
7.7%
p66
 
7.6%
d64
 
7.3%
a42
 
4.8%
o31
 
3.5%
Other values (16)177
20.3%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i97
10.9%
t92
10.3%
e83
9.3%
S82
9.2%
r73
 
8.2%
c67
 
7.5%
p66
 
7.4%
d64
 
7.2%
a42
 
4.7%
o31
 
3.5%
Other values (17)193
21.7%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size1008.0 B
English
35 
Chinese
23 
Russian
15 
Korean
10 
German
Other values (11)
22 

Length

Max length10
Median length7
Mean length6.818181818
Min length3

Characters and Unicode

Total characters750
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)4.5%

Sample

1st rowKorean
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowRussian

Common Values

ValueCountFrequency (%)
English35
31.8%
Chinese23
20.9%
Russian15
13.6%
Korean10
 
9.1%
German5
 
4.5%
Norwegian4
 
3.6%
Turkish4
 
3.6%
Arabic3
 
2.7%
Thai2
 
1.8%
Dutch2
 
1.8%
Other values (6)7
 
6.4%

Length

2022-05-09T21:16:07.736906image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english35
31.8%
chinese23
20.9%
russian15
13.6%
korean10
 
9.1%
german5
 
4.5%
norwegian4
 
3.6%
turkish4
 
3.6%
arabic3
 
2.7%
thai2
 
1.8%
dutch2
 
1.8%
Other values (6)7
 
6.4%

Most occurring characters

ValueCountFrequency (%)
s96
12.8%
n95
12.7%
i88
11.7%
e70
9.3%
h68
9.1%
a45
 
6.0%
g43
 
5.7%
l37
 
4.9%
E35
 
4.7%
r28
 
3.7%
Other values (22)145
19.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter641
85.5%
Uppercase Letter109
 
14.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s96
15.0%
n95
14.8%
i88
13.7%
e70
10.9%
h68
10.6%
a45
7.0%
g43
6.7%
l37
 
5.8%
r28
 
4.4%
u25
 
3.9%
Other values (10)46
7.2%
Uppercase Letter
ValueCountFrequency (%)
E35
32.1%
C23
21.1%
R15
13.8%
K10
 
9.2%
T7
 
6.4%
G5
 
4.6%
N4
 
3.7%
A3
 
2.8%
D2
 
1.8%
P2
 
1.8%
Other values (2)3
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Latin750
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s96
12.8%
n95
12.7%
i88
11.7%
e70
9.3%
h68
9.1%
a45
 
6.0%
g43
 
5.7%
l37
 
4.9%
E35
 
4.7%
r28
 
3.7%
Other values (22)145
19.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s96
12.8%
n95
12.7%
i88
11.7%
e70
9.3%
h68
9.1%
a45
 
6.0%
g43
 
5.7%
l37
 
4.9%
E35
 
4.7%
r28
 
3.7%
Other values (22)145
19.3%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct34
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Memory size1008.0 B
[]
21 
['Comedy']
16 
['Drama', 'Romance']
13 
['Drama', 'Comedy']
['Drama']
Other values (29)
49 

Length

Max length42
Median length39
Mean length17.02727273
Min length2

Characters and Unicode

Total characters1873
Distinct characters35
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)14.5%

Sample

1st row[]
2nd row['Drama', 'Crime', 'Mystery']
3rd row['Drama', 'Crime', 'Mystery']
4th row['Drama', 'Comedy']
5th row['Comedy', 'Family']

Common Values

ValueCountFrequency (%)
[]21
19.1%
['Comedy']16
14.5%
['Drama', 'Romance']13
11.8%
['Drama', 'Comedy']6
 
5.5%
['Drama']5
 
4.5%
['Sports']4
 
3.6%
['Drama', 'Action', 'Crime']4
 
3.6%
['Comedy', 'Adventure', 'Fantasy']3
 
2.7%
['Drama', 'Comedy', 'Romance']3
 
2.7%
['Food']3
 
2.7%
Other values (24)32
29.1%

Length

2022-05-09T21:16:07.846677image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama47
23.5%
comedy39
19.5%
romance22
11.0%
21
10.5%
adventure11
 
5.5%
fantasy10
 
5.0%
crime9
 
4.5%
action6
 
3.0%
mystery6
 
3.0%
sports4
 
2.0%
Other values (12)25
12.5%

Most occurring characters

ValueCountFrequency (%)
'358
19.1%
a142
 
7.6%
m123
 
6.6%
e112
 
6.0%
[110
 
5.9%
]110
 
5.9%
r92
 
4.9%
90
 
4.8%
,90
 
4.8%
o87
 
4.6%
Other values (25)559
29.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter928
49.5%
Other Punctuation448
23.9%
Uppercase Letter184
 
9.8%
Open Punctuation110
 
5.9%
Close Punctuation110
 
5.9%
Space Separator90
 
4.8%
Dash Punctuation3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a142
15.3%
m123
13.3%
e112
12.1%
r92
9.9%
o87
9.4%
y67
7.2%
n61
6.6%
d56
 
6.0%
t44
 
4.7%
c38
 
4.1%
Other values (7)106
11.4%
Uppercase Letter
ValueCountFrequency (%)
C50
27.2%
D48
26.1%
R22
12.0%
F20
 
10.9%
A20
 
10.9%
S8
 
4.3%
M7
 
3.8%
H4
 
2.2%
T2
 
1.1%
W1
 
0.5%
Other values (2)2
 
1.1%
Other Punctuation
ValueCountFrequency (%)
'358
79.9%
,90
 
20.1%
Open Punctuation
ValueCountFrequency (%)
[110
100.0%
Close Punctuation
ValueCountFrequency (%)
]110
100.0%
Space Separator
ValueCountFrequency (%)
90
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1112
59.4%
Common761
40.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a142
12.8%
m123
11.1%
e112
10.1%
r92
 
8.3%
o87
 
7.8%
y67
 
6.0%
n61
 
5.5%
d56
 
5.0%
C50
 
4.5%
D48
 
4.3%
Other values (19)274
24.6%
Common
ValueCountFrequency (%)
'358
47.0%
[110
 
14.5%
]110
 
14.5%
90
 
11.8%
,90
 
11.8%
-3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'358
19.1%
a142
 
7.6%
m123
 
6.6%
e112
 
6.0%
[110
 
5.9%
]110
 
5.9%
r92
 
4.9%
90
 
4.8%
,90
 
4.8%
o87
 
4.6%
Other values (25)559
29.8%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1008.0 B
Running
52 
Ended
51 
To Be Determined

Length

Max length16
Median length7
Mean length6.645454545
Min length5

Characters and Unicode

Total characters731
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowEnded
5th rowRunning

Common Values

ValueCountFrequency (%)
Running52
47.3%
Ended51
46.4%
To Be Determined7
 
6.4%

Length

2022-05-09T21:16:07.991786image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:08.083345image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
running52
41.9%
ended51
41.1%
to7
 
5.6%
be7
 
5.6%
determined7
 
5.6%

Most occurring characters

ValueCountFrequency (%)
n214
29.3%
d109
14.9%
e79
 
10.8%
i59
 
8.1%
R52
 
7.1%
u52
 
7.1%
g52
 
7.1%
E51
 
7.0%
14
 
1.9%
T7
 
1.0%
Other values (6)42
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter593
81.1%
Uppercase Letter124
 
17.0%
Space Separator14
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n214
36.1%
d109
18.4%
e79
 
13.3%
i59
 
9.9%
u52
 
8.8%
g52
 
8.8%
o7
 
1.2%
t7
 
1.2%
r7
 
1.2%
m7
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
R52
41.9%
E51
41.1%
T7
 
5.6%
B7
 
5.6%
D7
 
5.6%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin717
98.1%
Common14
 
1.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n214
29.8%
d109
15.2%
e79
 
11.0%
i59
 
8.2%
R52
 
7.3%
u52
 
7.3%
g52
 
7.3%
E51
 
7.1%
T7
 
1.0%
o7
 
1.0%
Other values (5)35
 
4.9%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII731
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n214
29.3%
d109
14.9%
e79
 
10.8%
i59
 
8.1%
R52
 
7.1%
u52
 
7.1%
g52
 
7.1%
E51
 
7.0%
14
 
1.9%
T7
 
1.0%
Other values (6)42
 
5.7%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct19
Distinct (%)25.0%
Missing34
Missing (%)30.9%
Infinite0
Infinite (%)0.0%
Mean41.52631579
Minimum5
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1008.0 B
2022-05-09T21:16:08.161809image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7
Q124.5
median45
Q345
95-th percentile60.5
Maximum240
Range235
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation30.75601781
Coefficient of variation (CV)0.7406392122
Kurtosis23.37522679
Mean41.52631579
Median Absolute Deviation (MAD)15
Skewness3.956515704
Sum3156
Variance945.9326316
MonotonicityNot monotonic
2022-05-09T21:16:08.241455image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4524
21.8%
308
 
7.3%
208
 
7.3%
607
 
6.4%
74
 
3.6%
424
 
3.6%
503
 
2.7%
403
 
2.7%
162
 
1.8%
252
 
1.8%
Other values (9)11
 
10.0%
(Missing)34
30.9%
ValueCountFrequency (%)
51
 
0.9%
74
3.6%
81
 
0.9%
101
 
0.9%
162
 
1.8%
181
 
0.9%
208
7.3%
231
 
0.9%
252
 
1.8%
308
7.3%
ValueCountFrequency (%)
2401
 
0.9%
1202
 
1.8%
621
 
0.9%
607
 
6.4%
512
 
1.8%
503
 
2.7%
4524
21.8%
424
 
3.6%
403
 
2.7%
308
 
7.3%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct41
Distinct (%)38.7%
Missing4
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean37.89622642
Minimum2
Maximum211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1008.0 B
2022-05-09T21:16:08.351547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile7.25
Q120
median41
Q345
95-th percentile63.5
Maximum211
Range209
Interquartile range (IQR)25

Descriptive statistics

Standard deviation27.5186272
Coefficient of variation (CV)0.7261574515
Kurtosis14.95461657
Mean37.89622642
Median Absolute Deviation (MAD)16
Skewness2.887629588
Sum4017
Variance757.2748428
MonotonicityNot monotonic
2022-05-09T21:16:08.457403image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
4522
20.0%
606
 
5.5%
306
 
5.5%
75
 
4.5%
214
 
3.6%
504
 
3.6%
174
 
3.6%
204
 
3.6%
424
 
3.6%
114
 
3.6%
Other values (31)43
39.1%
(Missing)4
 
3.6%
ValueCountFrequency (%)
21
 
0.9%
75
4.5%
81
 
0.9%
91
 
0.9%
102
 
1.8%
114
3.6%
122
 
1.8%
141
 
0.9%
151
 
0.9%
162
 
1.8%
ValueCountFrequency (%)
2111
 
0.9%
1202
 
1.8%
1021
 
0.9%
771
 
0.9%
641
 
0.9%
621
 
0.9%
606
5.5%
573
2.7%
561
 
0.9%
541
 
0.9%

_embedded_show_premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct64
Distinct (%)58.2%
Missing0
Missing (%)0.0%
Memory size1008.0 B
2020-12-17
14 
2020-12-10
 
7
2020-11-19
 
5
2020-11-26
 
4
2020-08-06
 
3
Other values (59)
77 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1100
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)41.8%

Sample

1st row2019-03-25
2nd row2018-10-29
3rd row2018-10-29
4th row2020-03-26
5th row2020-05-18

Common Values

ValueCountFrequency (%)
2020-12-1714
 
12.7%
2020-12-107
 
6.4%
2020-11-195
 
4.5%
2020-11-264
 
3.6%
2020-08-063
 
2.7%
2020-12-073
 
2.7%
2018-07-073
 
2.7%
2020-12-033
 
2.7%
2020-11-183
 
2.7%
2020-11-123
 
2.7%
Other values (54)62
56.4%

Length

2022-05-09T21:16:08.551309image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1714
 
12.7%
2020-12-107
 
6.4%
2020-11-195
 
4.5%
2020-11-264
 
3.6%
2020-08-063
 
2.7%
2020-12-073
 
2.7%
2018-07-073
 
2.7%
2020-12-033
 
2.7%
2020-11-183
 
2.7%
2020-11-123
 
2.7%
Other values (54)62
56.4%

Most occurring characters

ValueCountFrequency (%)
0271
24.6%
2253
23.0%
-220
20.0%
1197
17.9%
730
 
2.7%
828
 
2.5%
926
 
2.4%
325
 
2.3%
619
 
1.7%
417
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number880
80.0%
Dash Punctuation220
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0271
30.8%
2253
28.7%
1197
22.4%
730
 
3.4%
828
 
3.2%
926
 
3.0%
325
 
2.8%
619
 
2.2%
417
 
1.9%
514
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
-220
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0271
24.6%
2253
23.0%
-220
20.0%
1197
17.9%
730
 
2.7%
828
 
2.5%
926
 
2.4%
325
 
2.3%
619
 
1.7%
417
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0271
24.6%
2253
23.0%
-220
20.0%
1197
17.9%
730
 
2.7%
828
 
2.5%
926
 
2.4%
325
 
2.3%
619
 
1.7%
417
 
1.5%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct24
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size1008.0 B
nan
59 
2020-12-17
12 
2020-12-24
 
5
2021-01-14
 
4
2020-12-18
 
3
Other values (19)
27 

Length

Max length10
Median length3
Mean length6.245454545
Min length3

Characters and Unicode

Total characters687
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)10.9%

Sample

1st rownan
2nd row2021-01-07
3rd row2021-01-07
4th row2021-01-21
5th rownan

Common Values

ValueCountFrequency (%)
nan59
53.6%
2020-12-1712
 
10.9%
2020-12-245
 
4.5%
2021-01-144
 
3.6%
2020-12-183
 
2.7%
2021-10-073
 
2.7%
2020-12-282
 
1.8%
2021-01-042
 
1.8%
2020-12-222
 
1.8%
2021-01-022
 
1.8%
Other values (14)16
 
14.5%

Length

2022-05-09T21:16:08.665611image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan59
53.6%
2020-12-1712
 
10.9%
2020-12-245
 
4.5%
2021-01-144
 
3.6%
2020-12-183
 
2.7%
2021-10-073
 
2.7%
2021-01-022
 
1.8%
2021-01-072
 
1.8%
2020-12-302
 
1.8%
2020-12-222
 
1.8%
Other values (14)16
 
14.5%

Most occurring characters

ValueCountFrequency (%)
2152
22.1%
n118
17.2%
0116
16.9%
-102
14.8%
195
13.8%
a59
 
8.6%
719
 
2.8%
412
 
1.7%
87
 
1.0%
53
 
0.4%
Other values (2)4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number408
59.4%
Lowercase Letter177
25.8%
Dash Punctuation102
 
14.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2152
37.3%
0116
28.4%
195
23.3%
719
 
4.7%
412
 
2.9%
87
 
1.7%
53
 
0.7%
32
 
0.5%
62
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
n118
66.7%
a59
33.3%
Dash Punctuation
ValueCountFrequency (%)
-102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common510
74.2%
Latin177
 
25.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2152
29.8%
0116
22.7%
-102
20.0%
195
18.6%
719
 
3.7%
412
 
2.4%
87
 
1.4%
53
 
0.6%
32
 
0.4%
62
 
0.4%
Latin
ValueCountFrequency (%)
n118
66.7%
a59
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII687
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2152
22.1%
n118
17.2%
0116
16.9%
-102
14.8%
195
13.8%
a59
 
8.6%
719
 
2.8%
412
 
1.7%
87
 
1.0%
53
 
0.4%
Other values (2)4
 
0.6%

_embedded_show_officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct77
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size1008.0 B
nan
13 
https://www.netflix.com/title/81383020
 
4
https://www.tvnow.de/serien/unter-freunden-stirbt-man-nicht-19005
 
4
https://www.beinconnect.com.tr/diziler/aile-sirketi
 
3
https://play.hbomax.com/series/urn:hbo:series:GXkyDLAgeBY7CZgEAACHO
 
3
Other values (72)
83 

Length

Max length250
Median length71
Mean length47.85454545
Min length3

Characters and Unicode

Total characters5264
Distinct characters75
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)55.5%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttps://premier.one/show/8405
3rd rowhttps://premier.one/show/8405
4th rowhttps://start.ru/watch/257-prichin-chtoby-zhit
5th rowhttps://www.kinopoisk.ru/series/1379016/

Common Values

ValueCountFrequency (%)
nan13
 
11.8%
https://www.netflix.com/title/813830204
 
3.6%
https://www.tvnow.de/serien/unter-freunden-stirbt-man-nicht-190054
 
3.6%
https://www.beinconnect.com.tr/diziler/aile-sirketi3
 
2.7%
https://play.hbomax.com/series/urn:hbo:series:GXkyDLAgeBY7CZgEAACHO3
 
2.7%
https://v.qq.com/detail/m/mzc00200gbahyn5.html2
 
1.8%
https://www.iqiyi.com/lib/m_213579814.html2
 
1.8%
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
1.8%
https://www.iqiyi.com/a_19rrhllpip.html2
 
1.8%
https://so.youku.com/search_video/q_%E9%A2%84%E6%94%AF%E6%9C%AA%E6%9D%A5?spm=a2hbt.13141534.left-title-content-wrap.5~A2
 
1.8%
Other values (67)73
66.4%

Length

2022-05-09T21:16:08.782684image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan13
 
11.8%
https://www.tvnow.de/serien/unter-freunden-stirbt-man-nicht-190054
 
3.6%
https://www.netflix.com/title/813830204
 
3.6%
https://www.beinconnect.com.tr/diziler/aile-sirketi3
 
2.7%
https://play.hbomax.com/series/urn:hbo:series:gxkydlageby7czgeaacho3
 
2.7%
https://premier.one/show/84052
 
1.8%
https://www.kinopoisk.ru/series/13790162
 
1.8%
https://premier.one/show/123392
 
1.8%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
1.8%
https://www.wavve.com/player/vod?programid=c9901_c99000000047&page=12
 
1.8%
Other values (67)73
66.4%

Most occurring characters

ValueCountFrequency (%)
/394
 
7.5%
t382
 
7.3%
e267
 
5.1%
s265
 
5.0%
w221
 
4.2%
.207
 
3.9%
o202
 
3.8%
h193
 
3.7%
i192
 
3.6%
p170
 
3.2%
Other values (65)2771
52.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3354
63.7%
Other Punctuation823
 
15.6%
Decimal Number595
 
11.3%
Uppercase Letter352
 
6.7%
Dash Punctuation82
 
1.6%
Math Symbol35
 
0.7%
Connector Punctuation23
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t382
 
11.4%
e267
 
8.0%
s265
 
7.9%
w221
 
6.6%
o202
 
6.0%
h193
 
5.8%
i192
 
5.7%
p170
 
5.1%
a158
 
4.7%
n155
 
4.6%
Other values (16)1149
34.3%
Uppercase Letter
ValueCountFrequency (%)
A43
 
12.2%
D27
 
7.7%
C25
 
7.1%
E23
 
6.5%
P18
 
5.1%
L16
 
4.5%
T15
 
4.3%
Z15
 
4.3%
B14
 
4.0%
F14
 
4.0%
Other values (16)142
40.3%
Decimal Number
ValueCountFrequency (%)
198
16.5%
075
12.6%
363
10.6%
961
10.3%
557
9.6%
457
9.6%
850
8.4%
650
8.4%
248
8.1%
736
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/394
47.9%
.207
25.2%
:135
 
16.4%
%57
 
6.9%
?18
 
2.2%
&8
 
1.0%
#2
 
0.2%
!2
 
0.2%
Math Symbol
ValueCountFrequency (%)
=31
88.6%
~2
 
5.7%
+2
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
-82
100.0%
Connector Punctuation
ValueCountFrequency (%)
_23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3706
70.4%
Common1558
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t382
 
10.3%
e267
 
7.2%
s265
 
7.2%
w221
 
6.0%
o202
 
5.5%
h193
 
5.2%
i192
 
5.2%
p170
 
4.6%
a158
 
4.3%
n155
 
4.2%
Other values (42)1501
40.5%
Common
ValueCountFrequency (%)
/394
25.3%
.207
13.3%
:135
 
8.7%
198
 
6.3%
-82
 
5.3%
075
 
4.8%
363
 
4.0%
961
 
3.9%
557
 
3.7%
457
 
3.7%
Other values (13)329
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII5264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/394
 
7.5%
t382
 
7.3%
e267
 
5.1%
s265
 
5.0%
w221
 
4.2%
.207
 
3.9%
o202
 
3.8%
h193
 
3.7%
i192
 
3.6%
p170
 
3.2%
Other values (65)2771
52.6%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION

Distinct50
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.83636364
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1008.0 B
2022-05-09T21:16:08.902837image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q115
median34
Q358.75
95-th percentile91.65
Maximum100
Range99
Interquartile range (IQR)43.75

Descriptive statistics

Standard deviation28.05418325
Coefficient of variation (CV)0.7223689507
Kurtosis-0.7837724191
Mean38.83636364
Median Absolute Deviation (MAD)19.5
Skewness0.620103632
Sum4272
Variance787.0371977
MonotonicityNot monotonic
2022-05-09T21:16:09.014645image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
159
 
8.2%
186
 
5.5%
796
 
5.5%
396
 
5.5%
445
 
4.5%
145
 
4.5%
295
 
4.5%
344
 
3.6%
13
 
2.7%
543
 
2.7%
Other values (40)58
52.7%
ValueCountFrequency (%)
13
2.7%
21
 
0.9%
32
1.8%
42
1.8%
51
 
0.9%
62
1.8%
71
 
0.9%
82
1.8%
101
 
0.9%
111
 
0.9%
ValueCountFrequency (%)
1002
 
1.8%
981
 
0.9%
941
 
0.9%
932
 
1.8%
901
 
0.9%
872
 
1.8%
841
 
0.9%
796
5.5%
781
 
0.9%
771
 
0.9%

_embedded_show_dvdCountry
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1008.0 B
nan
109 
{'name': 'Korea, Republic of', 'code': 'KR', 'timezone': 'Asia/Seoul'}
 
1

Length

Max length70
Median length3
Mean length3.609090909
Min length3

Characters and Unicode

Total characters397
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan109
99.1%
{'name': 'Korea, Republic of', 'code': 'KR', 'timezone': 'Asia/Seoul'}1
 
0.9%

Length

2022-05-09T21:16:09.150218image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:09.233414image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan109
93.2%
name1
 
0.9%
korea1
 
0.9%
republic1
 
0.9%
of1
 
0.9%
code1
 
0.9%
kr1
 
0.9%
timezone1
 
0.9%
asia/seoul1
 
0.9%

Most occurring characters

ValueCountFrequency (%)
n220
55.4%
a112
28.2%
'12
 
3.0%
e7
 
1.8%
7
 
1.8%
o5
 
1.3%
i3
 
0.8%
:3
 
0.8%
,3
 
0.8%
R2
 
0.5%
Other values (18)23
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter363
91.4%
Other Punctuation19
 
4.8%
Space Separator7
 
1.8%
Uppercase Letter6
 
1.5%
Open Punctuation1
 
0.3%
Close Punctuation1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n220
60.6%
a112
30.9%
e7
 
1.9%
o5
 
1.4%
i3
 
0.8%
c2
 
0.6%
l2
 
0.6%
u2
 
0.6%
m2
 
0.6%
p1
 
0.3%
Other values (7)7
 
1.9%
Other Punctuation
ValueCountFrequency (%)
'12
63.2%
:3
 
15.8%
,3
 
15.8%
/1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
R2
33.3%
K2
33.3%
A1
16.7%
S1
16.7%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
{1
100.0%
Close Punctuation
ValueCountFrequency (%)
}1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin369
92.9%
Common28
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n220
59.6%
a112
30.4%
e7
 
1.9%
o5
 
1.4%
i3
 
0.8%
R2
 
0.5%
c2
 
0.5%
l2
 
0.5%
u2
 
0.5%
K2
 
0.5%
Other values (11)12
 
3.3%
Common
ValueCountFrequency (%)
'12
42.9%
7
25.0%
:3
 
10.7%
,3
 
10.7%
{1
 
3.6%
/1
 
3.6%
}1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII397
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n220
55.4%
a112
28.2%
'12
 
3.0%
e7
 
1.8%
7
 
1.8%
o5
 
1.3%
i3
 
0.8%
:3
 
0.8%
,3
 
0.8%
R2
 
0.5%
Other values (18)23
 
5.8%

_embedded_show_summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct75
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Memory size1008.0 B
nan
11 
<p>Comedian Andrew Schulz takes on the year's most divisive topics in this fearlessly unfiltered and irreverent four-part special.</p>
 
4
<p>Hermann has excellent prospects of winning the Nobel Prize in Economics. If only he hadn't died shortly before the award winner was announced. The dead don't win prizes.</p>
 
4
<p>Set in a world of anthropomorphic animals, Summer Camp Island follows two best friends Oscar, and Hedgehog, and Oscar who are dropped off at a surreal summer camp. The camp is a host to many odd occurrences such as: camp counselors who are composed of popular girls who know magic, horses that transform into unicorns, talking sharks, post-it notes that lead to other dimensions and nosy monsters that live under the bed. Oscar and Hedgehog must contend with these out of place events and make their stay at camp worthwhile.</p>
 
3
<p>Harun and Hande are brothers with opposite characters. Hande is a professional business woman in the tourism industry.</p>
 
3
Other values (70)
85 

Length

Max length978
Median length471.5
Mean length320.3
Min length3

Characters and Unicode

Total characters35233
Distinct characters102
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)50.0%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>
3rd row<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>
4th row<p>When terminal cancer patient Zhenya unexpectedly receives a clean bill of health, she can't believe it. She's in remission. But then her life implodes. Homeless, unemployed, and newly single - she stumbles across a list she wrote while she was sick of things she wanted to do when she got better. 257 of them - and now she won't give up until she checks off them all!</p>
5th row<p>Stories about friendship and adventures of charming round heroes. Fun and musical, unexpected and dreamy, homely and adventurous. The whole world in one cozy chamomile valley.</p>

Common Values

ValueCountFrequency (%)
nan11
 
10.0%
<p>Comedian Andrew Schulz takes on the year's most divisive topics in this fearlessly unfiltered and irreverent four-part special.</p>4
 
3.6%
<p>Hermann has excellent prospects of winning the Nobel Prize in Economics. If only he hadn't died shortly before the award winner was announced. The dead don't win prizes.</p>4
 
3.6%
<p>Set in a world of anthropomorphic animals, Summer Camp Island follows two best friends Oscar, and Hedgehog, and Oscar who are dropped off at a surreal summer camp. The camp is a host to many odd occurrences such as: camp counselors who are composed of popular girls who know magic, horses that transform into unicorns, talking sharks, post-it notes that lead to other dimensions and nosy monsters that live under the bed. Oscar and Hedgehog must contend with these out of place events and make their stay at camp worthwhile.</p>3
 
2.7%
<p>Harun and Hande are brothers with opposite characters. Hande is a professional business woman in the tourism industry.</p>3
 
2.7%
<p>Strange occurrences afflict a group of people after they purchase items on a shopping website from the future. </p>2
 
1.8%
<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>2
 
1.8%
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>2
 
1.8%
<p>A story that follows a detective in the major crimes division of Nan Xing City Police Department. Together with a woman who has super memory, he upholds the law one case at a time in solving murders, burglaries and bringing down a narcotics manufacturing facility. Jing Chu is a young and capable detective. Due to his repeated merits from cracking big cases, he is promoted to the position of major crimes division vice-captain at Nan Xing city and starts to work alongside his new team. Because of a murder case, he meets Yang Mian Mian, a young woman who possesses a photographic memory. He soon realizes that Mian Mian seems to have a deep connection to his father's mysterious death many years ago. Meanwhile, a famous blogger and a member of an idol girl group die</p>2
 
1.8%
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>2
 
1.8%
Other values (65)75
68.2%

Length

2022-05-09T21:16:09.329291image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the281
 
4.8%
and217
 
3.7%
a208
 
3.5%
to149
 
2.5%
of143
 
2.4%
in108
 
1.8%
is73
 
1.2%
with66
 
1.1%
his62
 
1.0%
that52
 
0.9%
Other values (1776)4555
77.0%

Most occurring characters

ValueCountFrequency (%)
5791
16.4%
e3234
 
9.2%
a2247
 
6.4%
t2178
 
6.2%
n2069
 
5.9%
o2038
 
5.8%
i1968
 
5.6%
s1808
 
5.1%
r1664
 
4.7%
h1479
 
4.2%
Other values (92)10757
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter26576
75.4%
Space Separator5808
 
16.5%
Uppercase Letter1090
 
3.1%
Other Punctuation1018
 
2.9%
Math Symbol580
 
1.6%
Dash Punctuation61
 
0.2%
Decimal Number56
 
0.2%
Format28
 
0.1%
Close Punctuation7
 
< 0.1%
Open Punctuation7
 
< 0.1%
Other values (2)2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3234
12.2%
a2247
 
8.5%
t2178
 
8.2%
n2069
 
7.8%
o2038
 
7.7%
i1968
 
7.4%
s1808
 
6.8%
r1664
 
6.3%
h1479
 
5.6%
l1069
 
4.0%
Other values (30)6822
25.7%
Uppercase Letter
ValueCountFrequency (%)
T127
 
11.7%
S116
 
10.6%
A71
 
6.5%
M66
 
6.1%
C60
 
5.5%
X55
 
5.0%
H53
 
4.9%
J48
 
4.4%
B47
 
4.3%
D38
 
3.5%
Other values (17)409
37.5%
Other Punctuation
ValueCountFrequency (%)
,382
37.5%
.305
30.0%
/153
15.0%
'78
 
7.7%
"48
 
4.7%
:18
 
1.8%
!14
 
1.4%
?9
 
0.9%
;5
 
0.5%
&3
 
0.3%
Other values (3)3
 
0.3%
Decimal Number
ValueCountFrequency (%)
015
26.8%
110
17.9%
27
12.5%
96
 
10.7%
55
 
8.9%
34
 
7.1%
43
 
5.4%
63
 
5.4%
82
 
3.6%
71
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
-50
82.0%
9
 
14.8%
2
 
3.3%
Space Separator
ValueCountFrequency (%)
5791
99.7%
 17
 
0.3%
Math Symbol
ValueCountFrequency (%)
>290
50.0%
<290
50.0%
Format
ValueCountFrequency (%)
28
100.0%
Close Punctuation
ValueCountFrequency (%)
)7
100.0%
Open Punctuation
ValueCountFrequency (%)
(7
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin27655
78.5%
Common7567
 
21.5%
Cyrillic11
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3234
11.7%
a2247
 
8.1%
t2178
 
7.9%
n2069
 
7.5%
o2038
 
7.4%
i1968
 
7.1%
s1808
 
6.5%
r1664
 
6.0%
h1479
 
5.3%
l1069
 
3.9%
Other values (47)7901
28.6%
Common
ValueCountFrequency (%)
5791
76.5%
,382
 
5.0%
.305
 
4.0%
>290
 
3.8%
<290
 
3.8%
/153
 
2.0%
'78
 
1.0%
-50
 
0.7%
"48
 
0.6%
28
 
0.4%
Other values (25)152
 
2.0%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
е1
9.1%
м1
9.1%
т1
9.1%
я1
9.1%
к1
9.1%
с1
9.1%
ж1
9.1%
у1
9.1%
М1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII35158
99.8%
Punctuation41
 
0.1%
None23
 
0.1%
Cyrillic11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5791
16.5%
e3234
 
9.2%
a2247
 
6.4%
t2178
 
6.2%
n2069
 
5.9%
o2038
 
5.8%
i1968
 
5.6%
s1808
 
5.1%
r1664
 
4.7%
h1479
 
4.2%
Other values (71)10682
30.4%
Punctuation
ValueCountFrequency (%)
28
68.3%
9
 
22.0%
2
 
4.9%
1
 
2.4%
1
 
2.4%
None
ValueCountFrequency (%)
 17
73.9%
é2
 
8.7%
å1
 
4.3%
ê1
 
4.3%
ã1
 
4.3%
ö1
 
4.3%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
е1
9.1%
м1
9.1%
т1
9.1%
я1
9.1%
к1
9.1%
с1
9.1%
ж1
9.1%
у1
9.1%
М1
9.1%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION

Distinct84
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1633537622
Minimum1607964656
Maximum1652126507
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1008.0 B
2022-05-09T21:16:09.480652image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1607964656
5-th percentile1609277410
Q11613286265
median1640102924
Q31648217029
95-th percentile1651890656
Maximum1652126507
Range44161851
Interquartile range (IQR)34930764.25

Descriptive statistics

Standard deviation16620143.33
Coefficient of variation (CV)0.01017432541
Kurtosis-1.56704901
Mean1633537622
Median Absolute Deviation (MAD)10756662
Skewness-0.4181877412
Sum1.796891384 × 1011
Variance2.762291644 × 1014
MonotonicityNot monotonic
2022-05-09T21:16:09.685556image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16089997384
 
3.6%
16131493034
 
3.6%
16393002023
 
2.7%
16407890403
 
2.7%
16184666822
 
1.8%
16482170292
 
1.8%
16491780842
 
1.8%
16097998962
 
1.8%
16357351792
 
1.8%
16097847492
 
1.8%
Other values (74)84
76.4%
ValueCountFrequency (%)
16079646561
 
0.9%
16084990071
 
0.9%
16089997384
3.6%
16096167881
 
0.9%
16096488852
1.8%
16096716402
1.8%
16097847492
1.8%
16097998962
1.8%
16101108412
1.8%
16109073001
 
0.9%
ValueCountFrequency (%)
16521265071
0.9%
16520679311
0.9%
16520165431
0.9%
16520047591
0.9%
16519813431
0.9%
16519332091
0.9%
16518386471
0.9%
16517773161
0.9%
16517491651
0.9%
16514293371
0.9%

_links_self_href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1008.0 B
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/2176148
 
1
https://api.tvmaze.com/episodes/1996399
 
1
https://api.tvmaze.com/episodes/1955318
 
1
https://api.tvmaze.com/episodes/1996786
 
1
Other values (105)
105 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4290
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.9%
https://api.tvmaze.com/episodes/21761481
 
0.9%
https://api.tvmaze.com/episodes/19963991
 
0.9%
https://api.tvmaze.com/episodes/19553181
 
0.9%
https://api.tvmaze.com/episodes/19967861
 
0.9%
https://api.tvmaze.com/episodes/19493361
 
0.9%
https://api.tvmaze.com/episodes/19493351
 
0.9%
https://api.tvmaze.com/episodes/19493341
 
0.9%
https://api.tvmaze.com/episodes/19493331
 
0.9%
https://api.tvmaze.com/episodes/19493321
 
0.9%
Other values (100)100
90.9%

Length

2022-05-09T21:16:09.796661image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.9%
https://api.tvmaze.com/episodes/23244331
 
0.9%
https://api.tvmaze.com/episodes/19954051
 
0.9%
https://api.tvmaze.com/episodes/20077601
 
0.9%
https://api.tvmaze.com/episodes/19857891
 
0.9%
https://api.tvmaze.com/episodes/20396221
 
0.9%
https://api.tvmaze.com/episodes/20396231
 
0.9%
https://api.tvmaze.com/episodes/23244271
 
0.9%
https://api.tvmaze.com/episodes/23244281
 
0.9%
https://api.tvmaze.com/episodes/23244291
 
0.9%
Other values (100)100
90.9%

Most occurring characters

ValueCountFrequency (%)
/440
 
10.3%
p330
 
7.7%
s330
 
7.7%
e330
 
7.7%
t330
 
7.7%
o220
 
5.1%
a220
 
5.1%
i220
 
5.1%
.220
 
5.1%
m220
 
5.1%
Other values (16)1430
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2750
64.1%
Other Punctuation770
 
17.9%
Decimal Number770
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p330
12.0%
s330
12.0%
e330
12.0%
t330
12.0%
o220
8.0%
a220
8.0%
i220
8.0%
m220
8.0%
h110
 
4.0%
d110
 
4.0%
Other values (3)330
12.0%
Decimal Number
ValueCountFrequency (%)
9119
15.5%
2115
14.9%
199
12.9%
099
12.9%
367
8.7%
663
8.2%
862
8.1%
753
6.9%
449
6.4%
544
 
5.7%
Other Punctuation
ValueCountFrequency (%)
/440
57.1%
.220
28.6%
:110
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2750
64.1%
Common1540
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/440
28.6%
.220
14.3%
9119
 
7.7%
2115
 
7.5%
:110
 
7.1%
199
 
6.4%
099
 
6.4%
367
 
4.4%
663
 
4.1%
862
 
4.0%
Other values (3)146
 
9.5%
Latin
ValueCountFrequency (%)
p330
12.0%
s330
12.0%
e330
12.0%
t330
12.0%
o220
8.0%
a220
8.0%
i220
8.0%
m220
8.0%
h110
 
4.0%
d110
 
4.0%
Other values (3)330
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/440
 
10.3%
p330
 
7.7%
s330
 
7.7%
e330
 
7.7%
t330
 
7.7%
o220
 
5.1%
a220
 
5.1%
i220
 
5.1%
.220
 
5.1%
m220
 
5.1%
Other values (16)1430
33.3%

Interactions

2022-05-09T21:16:00.689398image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:23.107387image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:33.145076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:36.928711image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:40.577954image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:44.007960image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:53.089301image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:55.512103image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:58.176824image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:01.779064image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:25.262682image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:34.699237image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:38.447048image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:41.914297image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:46.910367image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:54.100842image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:56.600998image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:59.153152image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:01.993230image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:25.972056image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:34.877984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:38.636275image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:42.079536image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:47.473678image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:54.225137image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:56.730369image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:59.256611image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:02.105407image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:26.725445image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:35.045062image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:38.818670image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:42.200555image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:48.060548image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:54.345939image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:56.841090image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:59.362638image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:02.208024image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:28.290210image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:35.197978image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:38.980961image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:42.314226image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:48.600608image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:54.458500image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:57.044054image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:59.473289image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:02.980616image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:30.085460image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:36.221343image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:40.019450image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:43.347768image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:50.945982image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:55.061624image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:57.759084image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:00.275053image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:03.084066image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:30.820054image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:36.373308image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:40.166380image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:43.477939image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:51.348297image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:55.175179image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:57.856132image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:00.377525image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:03.184948image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:31.591959image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:36.526764image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:40.293306image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:43.744503image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:51.991438image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:55.301721image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:57.967694image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:00.473262image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:03.318080image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:32.340831image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:36.660547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:40.440929image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:43.870463image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:52.505456image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:55.412395image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:15:58.085098image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:00.577847image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:16:09.874454image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:16:10.003124image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:16:10.129490image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:16:10.302515image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:16:10.522882image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:16:03.514071image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:16:04.243919image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:16:04.493278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:16:04.633323image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
01988861https://www.tvmaze.com/episodes/1988861/sim-for-you-4x23-chanyeols-episode-23Chanyeol's Episode 234.023.0regular2020-12-1706:002020-12-16T21:00:00+00:0016.0None<p><b>#Scared Meㅇㅍㅇ #Under The Sea♬ #The Last Supper</b></p>41648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25nanhttps://www.vlive.tv/video/12163771.0nan<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1.608499e+09https://api.tvmaze.com/episodes/1977902
11977892https://www.tvmaze.com/episodes/1977892/obycnaa-zensina-2x01-seria-10Серия 102.01.0regular2020-12-1710:002020-12-16T22:00:00+00:0036.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723163.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723163.jpg'}nan39115https://www.tvmaze.com/shows/39115/obycnaa-zensinaОбычная женщинаScriptedRussian['Drama', 'Crime', 'Mystery']Ended50.048.02018-10-292021-01-07https://premier.one/show/840536.0nan<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>1.610111e+09https://api.tvmaze.com/episodes/2015818
21977898https://www.tvmaze.com/episodes/1977898/obycnaa-zensina-2x02-seria-11Серия 112.02.0regular2020-12-1710:002020-12-16T22:00:00+00:0045.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723164.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723164.jpg'}nan39115https://www.tvmaze.com/shows/39115/obycnaa-zensinaОбычная женщинаScriptedRussian['Drama', 'Crime', 'Mystery']Ended50.048.02018-10-292021-01-07https://premier.one/show/840536.0nan<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>1.610111e+09https://api.tvmaze.com/episodes/1964000
31963998https://www.tvmaze.com/episodes/1963998/257-pricin-ctoby-zit-2x08-seria-21Серия 212.08.0regular2020-12-17nan2020-12-17T00:00:00+00:0025.0Nonenan43722https://www.tvmaze.com/shows/43722/257-pricin-ctoby-zit257 причин, чтобы житьScriptedRussian['Drama', 'Comedy']Ended25.024.02020-03-262021-01-21https://start.ru/watch/257-prichin-chtoby-zhit38.0nan<p>When terminal cancer patient Zhenya unexpectedly receives a clean bill of health, she can't believe it. She's in remission. But then her life implodes. Homeless, unemployed, and newly single - she stumbles across a list she wrote while she was sick of things she wanted to do when she got better. 257 of them - and now she won't give up until she checks off them all!</p>1.617284e+09https://api.tvmaze.com/episodes/1995405
41949910https://www.tvmaze.com/episodes/1949910/smesariki-novyj-sezon-1x31-emigrant-cast-1Эмигрант. Часть 11.031.0regular2020-12-17nan2020-12-17T00:00:00+00:006.0Nonenan48151https://www.tvmaze.com/shows/48151/smesariki-novyj-sezonСмешарики. Новый сезонAnimationRussian['Comedy', 'Family']Running7.07.02020-05-18nanhttps://www.kinopoisk.ru/series/1379016/79.0nan<p>Stories about friendship and adventures of charming round heroes. Fun and musical, unexpected and dreamy, homely and adventurous. The whole world in one cozy chamomile valley.</p>1.646905e+09https://api.tvmaze.com/episodes/2007760
51949911https://www.tvmaze.com/episodes/1949911/smesariki-novyj-sezon-1x32-zagЗаг1.032.0regular2020-12-17nan2020-12-17T00:00:00+00:006.0Nonenan48151https://www.tvmaze.com/shows/48151/smesariki-novyj-sezonСмешарики. Новый сезонAnimationRussian['Comedy', 'Family']Running7.07.02020-05-18nanhttps://www.kinopoisk.ru/series/1379016/79.0nan<p>Stories about friendship and adventures of charming round heroes. Fun and musical, unexpected and dreamy, homely and adventurous. The whole world in one cozy chamomile valley.</p>1.646905e+09https://api.tvmaze.com/episodes/1985789
61960728https://www.tvmaze.com/episodes/1960728/psih-1x07-osoznanieОсознание1.07.0regular2020-12-1712:002020-12-17T00:00:00+00:0061.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/301/752692.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/301/752692.jpg'}nan49280https://www.tvmaze.com/shows/49280/psihПсихScriptedRussian['Drama', 'Thriller']Ended62.062.02020-11-052020-12-24https://more.tv/psih29.0nan<p>Oleg is a metropolitan psychotherapist. Clients of the central district of Moscow line up to him. Only lately Oleg doesn't like them, he tolerates them. Midlife crisis, life with mom at 40, loss of self-esteem, drug addiction, irritability and growing aggression. None of the clients are aware of his problems. From the outside, he seems successful, happily married, wealthy. Nobody knows the truth.</p><p> </p><p>A year ago, his wife went missing. She has been gone for 384 days.</p>1.619195e+09https://api.tvmaze.com/episodes/2039622
71982405https://www.tvmaze.com/episodes/1982405/volk-1x07-seria-07Серия 071.07.0regular2020-12-17nan2020-12-17T00:00:00+00:0051.0Nonenan52181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian['Drama', 'Adventure', 'Mystery']Ended51.050.02020-12-072020-12-28https://premier.one/show/1233925.0nannan1.640436e+09https://api.tvmaze.com/episodes/2039623
81982406https://www.tvmaze.com/episodes/1982406/volk-1x08-seria-08Серия 081.08.0regular2020-12-17nan2020-12-17T00:00:00+00:0051.0Nonenan52181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian['Drama', 'Adventure', 'Mystery']Ended51.050.02020-12-072020-12-28https://premier.one/show/1233925.0nannan1.640436e+09https://api.tvmaze.com/episodes/2324427
91988012https://www.tvmaze.com/episodes/1988012/muzskaa-tema-1x01-seria-1Серия 11.01.0regular2020-12-1712:002020-12-17T00:00:00+00:0033.0Nonenan52520https://www.tvmaze.com/shows/52520/muzskaa-temaМужская темаTalk ShowRussian[]Ended30.030.02020-12-172020-12-25https://www.ivi.ru/watch/muzhskaya-tema3.0nan<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>1.616723e+09https://api.tvmaze.com/episodes/2324428

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
1001988001https://www.tvmaze.com/episodes/1988001/12-dates-of-christmas-s01-special-unwrappedUnwrapped1.0NaNinsignificant_special2020-12-17nan2020-12-17T17:00:00+00:0050.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723341.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723341.jpg'}<p>Hosted by D.J. "Shangela" Pierce (HBO's "We're Here," "RuPaul's Drag Race," "A Star Is Born"), this reunion special is a chance for Chad, Faith, Garrett and their love interests to unwrap everything that's gone down since last Christmas - from settling scores and revealing juicy behind-the-scenes stories to unmasking secret hookups and answering whether our couples stayed together... or said goodbye. With her trademark flair, humor and insight, Shangela stokes the Yule log fire.</p>45470https://www.tvmaze.com/shows/45470/12-dates-of-christmas12 Dates of ChristmasRealityEnglish['Romance']To Be DeterminedNaN43.02020-11-26nanhttps://play.hbomax.com/series/urn:hbo:series:GX6MzzwZycJYSwwEAAALF44.0nan<p><b>12 Dates of Christmas</b> is a holiday-inspired dating series set in a stunning winter wonderland. The series follows a cast of singles as they step into a real-life romantic comedy full of cozy sweaters, fireside cuddles, and mistletoe kisses, all arranged to help these souls find love - just in time for the holidays.</p>1.651110e+09https://api.tvmaze.com/episodes/2001671
1011980779https://www.tvmaze.com/episodes/1980779/tyler-perrys-ruthless-1x18-drinking-my-scotchDrinking My Scotch1.018.0regular2020-12-17nan2020-12-17T17:00:00+00:0043.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/731964.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/731964.jpg'}<p>Cynthia is in disbelief as she has finally caught Malcolm and Sarah in their long-standing affair. Ruth shares troubling news with Oliver about what really happens when the girls leave with Lilo. The Highest and River's relationship grows as Dikahn's dislike for River grows. </p>46668https://www.tvmaze.com/shows/46668/tyler-perrys-ruthlessTyler Perry's RuthlessScriptedEnglish['Drama']Running45.045.02020-03-19nanhttps://www.bet.plus/shows/tyler-perrys-ruthless93.0nan<p>The riveting story of a woman named Ruth who kidnaps her young daughter to join her in the dark underworld of a fanatical religious cult. Based on a character introduced in <i>Tyler Perry's The Oval</i>.</p>1.651981e+09https://api.tvmaze.com/episodes/2001672
1021950701https://www.tvmaze.com/episodes/1950701/texas-6-1x06-the-rivalryThe Rivalry1.06.0regular2020-12-17nan2020-12-17T17:00:00+00:0038.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726711.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726711.jpg'}<p>Perhaps the biggest rivalry in six-man football, the Greyhounds take on their cross-town rival, the Gordon Longhorns with all of Strawn watching.</p>51316https://www.tvmaze.com/shows/51316/texas-6Texas 6DocumentaryEnglish['Sports']RunningNaN36.02020-11-26nanhttps://www.cbs.com/shows/texas-6/54.0nan<p><b>Texas 6</b> takes place in Strawn, Texas and follows the Greyhounds, a high school six-man football team under the direction of Coach Dewaine Lee, as they attempt a three-peat for the 6-Man Football State Championship. While football remains the spine of Strawn, <i>Texas 6</i> ultimately depicts the spirit of a small town and a team that shows up for one another on and off the field.</p>1.637773e+09https://api.tvmaze.com/episodes/2001673
1031962891https://www.tvmaze.com/episodes/1962891/terror-lake-drive-1x04-something-about-ajSomething About AJ1.04.0regular2020-12-17nan2020-12-17T17:00:00+00:0060.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/363/908141.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/363/908141.jpg'}<p>AJ starts exuding some odd behavior as he protests to go back to Baltimore. Mounting inconsistencies emerge about Corey that leaves Sam in doubt.</p>51706https://www.tvmaze.com/shows/51706/terror-lake-driveTerror Lake DriveScriptedEnglish['Drama']Running60.060.02020-11-26nanhttps://allblk.tv/terrorlakedrive/75.0nan<p><b>Terror Lake Drive</b> follows a single mother from Baltimore who—on the heels of a recent pandemic and growing social unrest—relocates to Atlanta in an attempt to dodge her troubled past. As she settles into her new surroundings, she soon discovers that there are some things she can never run away from.</p>1.633448e+09https://api.tvmaze.com/episodes/2001674
1042008333https://www.tvmaze.com/episodes/2008333/for-the-love-of-jason-1x05-were-just-hanging-outWe're Just Hanging Out1.05.0regular2020-12-17nan2020-12-17T17:00:00+00:0025.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/732257.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/732257.jpg'}<p>Jason goes on a date with a woman who is forced to bring her young son along, and it's clear he has no home training. The date quickly goes bad and leads him back to Carmen. Bryan deals with the fallout of his relationship much to the crew's dismay. Lacy gets the call for a new opportunity. Carmen makes herself comfortable in Jason's life.</p>51899https://www.tvmaze.com/shows/51899/for-the-love-of-jasonFor the Love of JasonScriptedEnglish['Drama']RunningNaN25.02020-11-19nanhttps://allblk.tv/fortheloveofjason/41.0nan<p>Jason has always had it together. He's educated and financially stable with no baby mama drama. When he broke off his longtime relationship, he got caught up in the bachelor lifestyle, not realizing life was passing him by. One by one, his friends start settling down, leaving Jason the odd man out. He now feels pressure to catch up and finds himself in awkward dating encounters with women. Through it all, his friends are there to help him along the way.</p>1.646530e+09https://api.tvmaze.com/episodes/2007691
1052236493https://www.tvmaze.com/episodes/2236493/notruf-hafenkante-15x12-abistreichAbistreich15.012.0regular2020-12-1719:252020-12-17T18:25:00+00:0045.0Nonenan17046https://www.tvmaze.com/shows/17046/notruf-hafenkanteNotruf HafenkanteScriptedGerman['Drama', 'Crime']Running45.050.02007-01-04nanhttps://www.zdf.de/serien/notruf-hafenkante4.0nannan1.645352e+09https://api.tvmaze.com/episodes/2007692
1061977415https://www.tvmaze.com/episodes/1977415/goede-tijden-slechte-tijden-31x64-aflevering-6319Aflevering 631931.064.0regular2020-12-1720:002020-12-17T19:00:00+00:0023.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/720705.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/720705.jpg'}nan2504https://www.tvmaze.com/shows/2504/goede-tijden-slechte-tijdenGoede Tijden, Slechte TijdenScriptedDutch['Drama', 'Romance']Running23.025.01990-10-01nanhttp://gtst.nl/#!/77.0nannan1.651839e+09https://api.tvmaze.com/episodes/2031800
1071976647https://www.tvmaze.com/episodes/1976647/wwe-nxt-uk-2020-12-17-episode-51Episode 512020.051.0regular2020-12-1715:002020-12-17T20:00:00+00:0060.0Nonenan39053https://www.tvmaze.com/shows/39053/wwe-nxt-ukWWE NXT UKSportsEnglish[]Running60.060.02018-10-17nannan84.0nan<p>The one-hour episodes will feature the biggest names from NXT UK, including Pete Dunne, Mark Andrews, Rhea Ripley, Toni Storm, Tyler Bate, Trent Seven and Wolfgang. Joining the NXT UK broadcasting team as backstage interviewer is British broadcasting personality Radzi Chinyanganya, best known for hosting ITV game show "Cannonball," and in his ongoing role as a presenter of the world's longest-running children's TV show, the BBC's "Blue Peter." Calling the action are commentators Nigel McGuinness and Vic Joseph, joined by ring announcer Andy Shepherd and NXT UK General Manager, the legendary Johnny Saint.</p>1.652005e+09https://api.tvmaze.com/episodes/2034364
1082041990https://www.tvmaze.com/episodes/2041990/titan-fc-2020-12-17-titan-fc-66-assis-vs-hollowayTitan FC 66: Assis vs. Holloway2020.08.0regular2020-12-1722:002020-12-18T03:00:00+00:00120.0Nonenan16665https://www.tvmaze.com/shows/16665/titan-fcTitan FCSportsEnglish[]RunningNaN102.02006-03-11nanhttp://www.titanfighting.com4.0nan<p>Titan Fighting Championship is an American mixed martial arts promotion based out of Pompano Beach, FL. Their shows were originally run in and near Kansas City and have since expanded to include venues all over North America and eventually, international locations.</p>1.648432e+09https://api.tvmaze.com/episodes/2035877
1092008338https://www.tvmaze.com/episodes/2008338/beyond-the-pole-s01-special-living-under-lockdownLiving Under Lockdown1.0NaNinsignificant_special2020-12-1722:002020-12-18T03:00:00+00:0060.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/378/946214.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/378/946214.jpg'}<p>From virtual strip clubs to OnlyFans, the queens of hustle and grind are back for a unique behind the scenes look at their journey to financial freedom. When Atlanta shuts down its famous nightlife scene due to a global pandemic, the clubs' exotic dancers, bartenders, and bottle girls struggle to find income streams. Ms. Dime, Angel Kake, Empress, and Lyric self-document their fight for survival.</p><p><i>Premiered on WEtv</i></p>40633https://www.tvmaze.com/shows/40633/beyond-the-poleBeyond the PoleRealityEnglish[]Ended60.060.02019-01-032021-08-05https://allblk.tv/beyondthepole41.0nan<p>The day and the life of six popular Atlanta strippers trying desperately to start businesses off the pole.</p>1.640896e+09https://api.tvmaze.com/episodes/2035880